The Econophysics Blog

Smoke & Mirrors (or What The Pink Panther Can Teach Us About the Market Meltdown)

2008-01-27T21:28:00.000Z

What a week! Last week began with an almost unprecedented plunge in global stockmarkets that stretched from Hong Kong to Frankfurt (and places in between) that led to the sharpest interest rate cut in the history of the US Federal Reserve (21 - 22 January 2008). The week finished with the venerable French bank, Societe Generale, announcing that it had lost $7.2 billion -- a figure that easily exceeds the GDP of several countries and rivals Harvard's endowment -- because of the actions of a 'rogue trader,' Monsieur Jerome Kerviel. (Aside: The two events may have been related.)

So how do we make sense of these events? For that matter, how do we get our minds around the whole credit crisis and its messy consequences? The answer: Think of the Pink Panther.

For those of you who are not cinephiles (movie lovers), The Pink Panther (the original version and not the one with Steve Martin) was a 1963 movie starring David Niven as the brilliant jewel thief, Sir Charles Lytton, a.k.a. 'the Phantom,' who planned on stealing a rare diamond, named the Pink Panther. His nemesis was one Inspector Jacques Clouseau, played by the late, great British comedic actor Peter Sellers.

Originally, The Pink Panther was suppose to be a star vehicle for David Niven's character, the Phantom. The Phantom was supposed to be the criminal version of James Bond who would have a movie franchise built around his criminal exploits. In reality, what happened was that Peter Sellers' brilliant performance as the bumbling but preternaturally lucky Inspector Clouseau was so popular that subsequent movies in the Pink Panther series was built around his character. Inspector Clouseau -- rather than the Phantom -- became a household name, recognized by people who have never seen the movies, and became a near universal cultural reference.

And that's the problem. The problem that we are having in analyzing what is happening to the markets during this credit crisis and general collapse of confidence in financial markets is that we are focusing in on the Inspector Clouseaus rather than the Phantoms.

People -- especially during the annual meeting of financial, economic, and political 'luvies' at Davos, Switzerland -- have expressed incredulity at how Jerome Kerviel could have lost the equivalent of the GDP of several countries through bad trades and outright fraud. Some of the thoughts that have been expressed from Wall Street and the City (of London) to the ski slopes of Switzerland include: 'He couldn't have acted alone.' 'How much has he socked away?' 'He didn't even attend a Grandes Ecoles!'

My thoughts on these displays of incredulity are this: He probably did act alone. That is not to absolve the guilt of the Mandarins who did attend the Grandes Ecoles and run SocGen and much of France ... they fell asleep at the helm. But Jerome Kerviel probably knew enough about gaming the system from his experience with back-office work with processing and auditing trades to get away with it as long as he did.

I also believe that he didn't gain much financially from his endeavors. After all, if he did stash away billions (or even millions) of Euros from his fraudulent trades, then why didn't he run off to some exotic locale with an ex-model turned chanteusse in the style of another Frenchmen who's been in the news? His motivation was probably to cover up the fact that he made losing bets on the direction of equity futures. It probably had more to do with ego rather than financial gain. (Some insights into this was given by another infamous 'rogue trader,' Nick Leeson -- the man who brought down the venerable British bank, Barings -- during a recent interview with the BBC that was surprisingly candid and detailed.)

As for the final point, it's true that he didn't attend a Grandes Ecoles, but this brings us to what I call the Pink Panther problem. By focusing on the admitedly tantalizing narrative of some 'rogue trader' bumbling away billions of Euros, Pounds, Dollars, etc., we are missing what ought to be far more disturbing aspects of what is happening to us because of the crisis in the financial markets.

No, Jerome Kerviel didn't attend fancy schools and wasn't a member of the power elite. But what is the responsibility of those who have fancy credentials and connections in the current economic mess? It's easy to scapegoat some low-level employee in a trading outfit or some lowly mortgage broker or realtor straight out of Glengarry Glen Ross for the current troubles, but what about the higher-ups who are pocketing huge bonuses and/or severance packages and will land on their feet despite fubar-ing away billions if not trillions of dollars (all the while people are losing jobs and losing their homes)?

What about all of the supposedly non-rogue traders and derivatives salesmen who made decisions that were far more reprehensible and stupid than what Jerome Kerviel allegedly did? Those people aren't being arrested ... no, they're the ones who are running off to exotic locales with trophy wives/mistresses while they leave behind a trail of victims that lost a substantial chunk of what little they had.

What about the sanctimonious cheiftains of investment banks, hedge funds, etc., that ridicule single mothers, the lost youth of the inner cities and the countryside, and others who are less fortunate than they when they sincerely need help all the while these captains of industry are going around panhandling for money from goverment backed investment vehicles?

What about the politicians that looked the other way when all of this was going on? They weren't being wined and dined by the Jerome Kerviels of the world nor were they concerned about what would happen to ordinary Joes and Joannes that voted for them when the supposedly non-rogue, but (in some ways) far more crazy financial dealings of those who were wining and dining officials blew up. No, it was the business-world's equivalents of 'Sir Charles Lytton' that did attend the Grandes Ecoles, the Ivy Leagues, etc., that got our leaders and regulators to look the other way.

And looking the other way is at the heart of our crisis. One of the basic tricks of magicians is to use devices that distract the audiences' attention from what they should be focused in on in order to not get tricked ... smoke and mirrors. A good magician knows that human beings are more likely to be interested in the stumbling and bumbling Inspector Clouseau rather than the coldly calculating Phantom.

The mess that we are in is because we believed in a mirage, a possibility suggested in an excellent article by David Leonhardt of the New York Times. Just as Inspector Clouseau repeatedly escaped death by pure dumb luck, we had managed to escape financial disaster (until now that is) by Clouseau-esque good fortune. Sadly, Peter Sellers is no longer with us, and it is obvious now that the economy is also mortal.

People thought that the "spreading of financial risk, across institutions and around the world, had reduced the odds of a crisis" (from David Leonhardt's article). Quite the contrary, it is the spreading of financial risk that has led to the spreading of the crisis. Just as infectious diseases become more contagious when a virus or a bacteria takes advantage of the network effects of the interlinked relationships between their human hosts, financial contagion can now spread through more channels than in the past.

We were told that financial derivatives is another way of taming risk. Although derivatives can be validly used in risk and investment management, there are those who want to -- in the infamous, quasi-fictional words of Satyajit Das' 'Nero Tulip' -- lever up as much as possible via ever dizzying combinations of options, swaps, futures, special purpose entities, etc. In the recent past, we were lucky on a Clouseau-esque level to not have had all this 'hidden' leverage blow-up on us. Our luck ran out.

Risk can't be tamed. It can't be controled in some simplisitic, mechanstic way. That's the mirage we believed in. We put our faith in the good fortune of Jacques Clouseau all the while missing the thieves getting way with the loot.

Risk can't be waved away with a magic wand nor can we shuffle it off somewhere without it feeding back on us. Scapegoating some low-level flunky misses the point ... although there are plenty of villains (including, allegedly, Mr. Kerviel) ... because the really reprehensible characters will probably get away with it.

We can respect risk. We may be able to understand it on some level (although I doubt we can fully unravel its mysteries). But risk isn't subject to us, we are subject to it.

VIX Shows Greater Sense of Uncertainty in the Markets

2008-01-16T22:41:00.000Z

I just did some analysis of VIX (the index of the implied volatilities in S&P 500 options created by the Chicago Board of Options Exchange) data from 2004 to this Tuesday (15 Jan. 2008). The VIX is widely considered to be the one of the best indicators of the market's sentiment on volatility, risk, and uncertainty.

If you look at the chart I created (see below -- click it to see a larger image), you can clearly see that -- from late Summer of 2007 -- the market's consensus on volatilty has been elevated to a substantially higher level. Another thing that is striking from this chart I created is how 'jumpy' risk is. Not only are there sizable spikes but there seems to be some anecdotal evidence of what econometricians call 'regime switching.' In this case, the regime we have switched to is that of higher volatility and uncertainty in the marketplace.

These upward jumps and spikes in risk seems to coincide pretty well with the credit crises and other negative economic and financial news. Of course, this isn't a careful study of the data, but I thought I would offer up a tiny bit of real world financial data analysis to readers of this blog.

Google vs. New Hampshire: Prediction Markets & Networks

2008-01-13T19:45:00.000Z

As an American ex-pat living in the UK, I seem to be following the Presidential primary process with a greater degree of interest than I would have had I still been in the States. So when I read some articles recently about Google and a separate set of articles on how the pundits were surprised by Hillary Clinton's surprise victory over Barack Obama despite polls to the contrary, I thought there could be an interesting 'mash up' between these two seemingly unrelated issues. Oddly enough, the last week or so has shown that there are surprising commonalities between one of Google's business practises and how predictions of an Obama landslide failed to materialise.

Google encourages it's employees to use a prediction market to place bets on forecasts of events such as 'Will Google open a Russia office?' or 'How many users will Gmail have at the end of the quarter?' The reward for making correct predictions? Goobles (rhymes with rubles) which can be converted into prizes. Economists, Justin Wolfers (who has been featured on several blog posts on this site -- do a Google search of this blog), Eric Zitzewitz, and Bo Cogwill, wrote up a research report, Using Prediction Markets to Track Information Flows: Evidence From Google, that reaches an interesting conclusion: Information -- in the form of correlation in betting -- is "shared most easily and effectively among office neighbors, even at an Internet company where instant messaging and e-mail are generally preferred to face-to-face discussion," and that this type of information or social network -- based on "microgeography" (i.e., how people are [literally in this case] located in relation to each other) -- outweighs even friendship as a factor in information transmission within Google (as a business).

Although the use of prediction markets within Google is an interesting topic in it of itself, it got me thinking about how the findings from the research on Google's prediction markets might relate to making predictions about the electoral process -- especially, after the mini-debacle in New Hampshire. New York Times columnist, John Tierney wrote in his blog that prediction markets -- specifically Intratrade -- was the idea venue for coming up with accurate predictions in elections. Unfortunately for Mr. Tierney (and perhaps Intratrade as well), the results of the Democratic primary in New Hampshire made it, in John Tierney's words, "the wrong day to tout the Intratrade futures market." That's an understatement! (Although in fairness to Mr. Tierney and Intratrade, the tide started to turn toward Hillary at Intratrade a lot faster than it did in the news media.)

A less sanguine blog post was written by another New York Times columnist, David Leonhardt. In his post, Primary Predictions Popped, Mr. Leonhardt likened what happened on prediction markets, like Intratrade, where Barack Obama was given a greater than 95% chance of winning, to the bursting of "their version of the dot-com bubble." Part of the problem is that, as Mr. Leonhardt points out, the markets for these prediction markets are "thin" -- in stockmarket-speak, 'illiquid' -- which makes these markets especially vulnerable to bubbles and volatility.

Although I agree with Mr. Leonhardt, I think there is something else going on here -- which is precisely what the research shows on Google's prediction market -- the importance of the old real estate addage: 'Location, location, location.' In other words, the 'microgeography' -- or how people in a business or social environment interact with each other both by physical proximity and institutional strictures -- of how politicos, whether they be political operatives, journalists, pundits or 'experts', etc. -- can bias the information flow. Such swarming or coalescing of information flow can lead to bubbles in both political prediction (whether or not it takes place in a formal marketplace) and in the stockmarkets (this was one of the points that Didier Sornette made in his book, Why Stock Markets Crash: Critical Events in Complex Financial Systems [you can read my review of that book here]).

The New York Times article, Analyzing the New Hampshire Surprise (Jan. 10, 2008), by Jacques Steinberg and Janet Elder, seems to provide some evidence for my hypothesis. The article suggests that some political journalists and pundits were getting on the Barrack Obama bandwagon too soon (a particularly pointed example was Newsweek all-but annointing him on its front cover). This type of 'information cascade' may have at least indirectly contributed to incorrectly predicting the outcome of the Democratic primary in New Hampshire.

Perhaps the anecdote to these types of predictive mishaps is what Google does -- presumably based, in part, on its research into its own prediction markets -- with its employees: Move them around frequently. Political pundits, journalists, and operatives need to get out and about more often with people who are dis-similar to them rather than always hanging out with people who do more or less the same thing they do: making politics cynical and downright silly.

Putting a Face on the Victims of Credit Derivatives

2008-01-01T01:07:00.000Z

I came across an extremely interesting New York Times article this Sunday by Gretchen Morgenson: The Debt Crisis, Where It’s Least Expected (Dec. 30, 2007). One of the things I liked about this article is that it put a very sympathetic face -- the Indiana Children's Wish Fund -- to a very abstract and complex problem -- credit derivatives and the monsterous affect it has had on fueling the wildfire of the credit crises.

It turns out that this charity, which is dedicated to fulfilling the wishes of extremely ill children (many of them terminally ill), was tricked into investing in complex credit derivatives! It's the same old story: Unwitting small time investors lured into investments that promise higher yields at supposedly low risk; unbeknownst to them, they are writing options (i.e., could lose their shirts) in exchange for that slightly higher yield. But this time, the victims are truly sympathetic ... the director of the Wish Fund went out of her way to make sure the investments were as safe as CDs and money market funds. The (unscrupulous) broker -- no doubt selling her some propaganda about AAA rated mortgage-backed securities (we know what those ratings are worth ... zilch) -- bamboozled the fund into buying into credit derivatives as all hell was about to break lose.

This is one of the -- if not THE -- best articles I have read on the credit crises. There are many interesting aspects to this article. The one I found darkly humorous was mortgage-backed securities hedge fund 'hotshot,' John Devaney, owning a yacht called "Positive Carry." The name of the yacht is derived from the 'carry trade' ... and as I have written about this in the past (just do a search of the blog) ... this is essentially, as Nassim Nicholas Taleb so aptly puts it, "stepping in front of steamrollers to pick up pennies." Apparently, the steamroller finally caught up with "Positive Carry" ... apologies for a bit of schadenfreude.

As for the Indiana Children's Wish Fund, there is some good news. They were able to get a very quick settlement (thanks, in part, to the exposure by the New York Times) from their brokers. If anyone needed a concrete example of how the shameless marketing of credit derivatives to investors who have NO business getting mixed up with complex financial derivatives, then the Wish Fund serves as Exhibit A. Without the settlement, the credit crises would have meant that nine children's wishes would have gone unfulfilled. When you see a photo of a terminally ill child getting to meet Indiana Colt's quaterback, Peyton Manning ... sadly, the child in the photo died a few weeks after meeting his hero ... one can get a full sense of the gravity of the damage that some hotshot traders and derivatives salesmen have caused in ordinary people's lives on their way to buying yachts, luxury homes, etc.

Follow up to Mind Time

2007-12-16T23:23:00.000Z

I noticed an article -- Why Time Seems to Slow Down in Emergencies at Live Science (11 December 2007) -- that serves as an interesting follow-up to my previous blog post on 'mind time'.

The Live Science article discusses research being done at Baylor University on why people have the sensation that time 'slows down' during stressful situations. Those researchers believe that this neurological phenomenon is related to how memories are formed rather than a physiological reaction like increased adrenaline. Basically, they argue that our brains tend to imprint memories in a deeper way when we're under stress than in normal situations; this leads to the sensation that time 'stretches' under stressful situations.

Interesting research. I don't know if it fully explains the 'mind time' phenomenon, but it sounds like a reasonable explanation. By the way, there is also a short video of the experiment.

Book Review: Why Stock Markets Crash: Critical Events in Complex Financial Systems

2007-12-09T23:28:00.000Z

I have to admit that when I first (which was about 5 years ago) heard of UCLA geophysicist, Didier Sornette, and his book, Why Stock Markets Crash: Critical Events in Complex Financial Systems, I was skeptical. In deciding to write this book review, I reflected back on why I had that first impression. One of the reasons was that (and, recall, that this was before I moved to the UK from the US) I first heard about this book on the local tv news ... a highly unusual event since the local tv news normally covers car chases and celebrity punch-ups rather than sending their well-groomed reporters to chat up geophysics professors. Since television reporters --local or national -- are usually not renowned for their expertise in disseminating the research of physicists and mathematicians to the general public, the local news did a poor job of explaining in a 30 second sound-bite the monumental importance of this outstanding book.

In fairness to the local tv 'journalists,' they focused on an aspect of the book that made me skeptical then and, to some extent, makes me skeptical now: the last chapter of the book (chapter 10). But if we (temporarily) ignore the last chapter, Didier Sornette's book is the best book in the still nascent discipline of econophysics and one of the greatest contributions to the scientific understanding of markets that has ever been written.

The best one-line endorsement (although I will give a detailed review below) I can give this book is the following: Replace "stock" with any word you like ... "credit" or "mortgage" or "real estate" or "tulip" ... and you pretty much get a rock solid scientific explanation of why markets crash and why, like the geological faults that criss-cross California, they will inevitably rupture.

In this review, I will try to do what the local tv reporter should have done ... focus on chapters 1 to 9. I will deal with chapter 10 in due course.

---

A large portion of the early part of the book is spent on describing financial markets and how traditional financial economics models have failed to properly explain and predict market crashes. This may not sound too original since other books, more or less, have done the same thing. What is very original in this book is that -- rather than a lot of handwaving and limiting itself only to historical anecdotes -- it is not afraid to employ maths (sorry, British English) and physics to scientifically analyze the nature of crashes.

I should note at this point that the level of mathematics knowledge required to understand this book is somewhere near a good American high school level of math. Sornette, unlike other physicists who have written 'popular' books, doesn't subscribe to the apocryphal story about Stephen Hawking being told by his publisher that each equation that is added to his book leads to some proportionate drop in book sales (although Sornette's book is nowhere near as popular as A Brief History of Time ... although it should be!). That having been said, one can safely ignore most of the maths and still get a lot of insights from the book.

Having said that, if you happen to be comfortable with mathematics, then all the better because there is a lot of beautiful and interesting mathematics and physics in this book. Sornette is a real scientist rather than a mercenary that happens to use (quasi-) scientific tools in the pursuit of filthy lucre. Reading his book, one gets the sense that Sornette really loves maths and science, because he talks about things like Polya urn models, Benford's law, evolutionary psychology, and computer simulations of 'artificial life' that others writing in the field of quantitative finance either don't care to write about or write about carelessly.

He invests time in introducing the reader to the ideas of complexity theory and econophysics. Fractals, power laws, critical phenomena, etc., are carefully described in this part of the book. The fact that Didier Sornette is a geophysicist by training is perfect for studying market crashes since there are many fruitful analogies that can be drawn between earthquakes -- which can be best understood in the light of complexity theory -- and market tremors.

What I found useful in this part of the book is the critique of how econometricians have tried to deal with what are clearly non-Gaussian aspects of financial market data. Sornette is right to criticize GARCH (Generalized Autoregressive Conditional Heteroskedasticity -- for you nerds out there) because the fat tails that model tries to pick up aren't fat enough. Sornette is also right to point out that most of the linear correlations useful for arbitrage have been arbitraged away (and the only linear correlations useful for arbitrage involve such short time intervals that the costs doesn't justify chasing after them). What are really interesting then are non-linear 'correlations' (really, they're not correlations or covariances, but some sort of inter-relationships that are happening at higher statistical moments ... presuming 'moments' are even meaningful in that context) that manifest themselves when markets exhibit complex, critical behavior (i.e., there is some dynamic 'attractor' where financial agents are either bidding up towards, or -- in the current credit crises -- bidding down towards -- in a non-linear way).

Having laid the intellectual groundwork, in the middle to later parts of the book, Sornette uses these concepts -- along with other tools from econophysics -- to develop models to predict crashes. Let me repeat that: Sornette comes up with models that almost precisely predict crashes! And, it seems to work pretty well (so far). What Sornette does is to fit and calibrate financial market data to a highly non-linear model. These predictive models seem to have done a decent job of predicting market downturns in a timely manner.

What's more, these models are not described in a hand-waving, 'black box' manner in the book. He prints them (or at least the non-proprietary version) in the book. That alone should make people run out, digging into their wallets, to buy this and other books by Sornette.

But this is where the skeptic in me awakens. In Nassim Nicholas Taleb's The Black Swan, the careful reader may have noticed an 'inside joke' when Taleb -- who heartily endorses Sornette's book(s) (as I am doing as well) -- suggests that people not tell Sornette about Taleb's skepticism about predictive models so that Sornette won't stop creating his interesting models.

Let me throw in my 2 pence into that discussion among intellectual comrades ... Yes, I think Sornette and his models are brilliant and they are probably right and even useful, but almost any non-Gaussian model would do a better job than Gaussian methods of calibrating predictive models based on financial data. Sornette's models are probably a lot better than the other non-Gaussian or pseudo-non-Gaussian models out there (like GARCH, stochastic volatility, etc.) but -- like most models -- there is probably some model risk with Sornette's models as well and their overuse will -- as Fischer Black noted with the Black-Scholes option pricing model -- lead to noise trading and model breakdowns.

Which leads me to chapter 10. In chapter 10 -- which, if you will recall, is what the local tv reporter exclusively focused in on -- is where Sornette 'predicts' that the year 2050 is when the era of economic growth will end. This seems vaguely reminiscent of Nostradamus or the Book of Revelations in the Bible. Unlike Nostradamus or St. John, Sornette uses equations, time series data, and ideas from self-organized criticality to make his bold prediction.

Is he right? I don't know. Maybe he's right. Maybe he's wrong. That was what bothered me 5 years ago. Honestly, it still bothers me ... but much less so, and certainly not enough to give this book anything less than my highest endorsement and praise.

Why? Because this book and its author goes against the grain.

Look at all of the so-called 'quants' that were terribly wrong about credit derivative models. They used rubbish pseudo-science in a mercenary way, dressed it up with things like AAA ratings that weren't worth the paper they were printed on, and then went off and bought luxury yachts while the rest of us are left holding the bag. When confronted with their failures, they inevitably turn defensive. There is no genuine humility there. The same folks (or people who will be virtually indistinguishable from them) will lead us into another round of financial catastrophes. It may not be mortgages next time. Maybe it will be inflation linked derivatives. Maybe it will be commodity linked derivatives. Whatever. It will happen. To borrow a phrase from a Jarvis Cocker song, they will kill again.

But Sornette is different. He is a real scientist. Every page of his book is embued with a sense that this man loves science. He is applying genuine science -- physics, math, etc. -- to scientifically examine a phenomena that is often more earth-shaking and causes more damage than the earthquakes that a geophysicist is usually concerned with ... market crashes. Maybe he will be wrong. He is willing to risk it and be honest about it. He has the genuine humility of a genuine scientist. If his models don't work out, then he will acknowledge that and work to improve it rather than cynically 'putting lipstick on a pig.'

I own all of his books and I believe that they will be useful to me in my attempts to understand uncertainty. But if his models don't work out ... well, that's science. Sornette, as a real scientist, is willing to risk failure to know ... to understand ... to learn how the world works. When I finally put my initial skepticism aside and read the book, I got that feeling as well. Not only do I take solace in that, I am inspired by it.

Goldie Gets The Porridge (Everyone Else Will Get Lawsuits)

2007-12-06T23:40:00.000Z

Regulars to this blog will recognize that -- very early on in the current credit crises -- I diagnosed and laid out the problems and predicted how this crises would play out. Sadly, everything I foresaw happening has come to pass.

Anyone who doubts that credit derivatives (for the most part, mortgage backed securities) helped to inflate the bubble -- and are now magnifying the downturn to almost cataclysmic levels -- should read a recent New York Times article: Wary of Risk, Bankers Sold Shaky Mortgage Debt (Dec. 6, 2007). The part that I found most interesting -- but not surprising -- was that many prominent investment banks paid inflated prices to buy into mortgage deals that they could turn around and repackage into CDOs and sell to now embittered investors (which includes those banks themselves).

My next prediction: Lawsuits. It will be based on legal concepts like uberrima fides (utmost good-faith, in Latin) from insurance law. Banks relied on high-priced legal opinions from their favorite law firms -- not having case law and/or statutes to support their lucrative business of selling credit derivatives while washing their hands of being treated like insurers or guarantors of default risks -- to do what they did. Those legal opinions -- along with other practices of banks related to the credit derivatives business that can be challenged by lawyers -- will be challenged.

My advice to the I-banks: Don't believe your own bluffs. They shouldn't have loaded up on risk the way that they did. They should have hedged earlier and more earnestly. They shouldn't have bought at bloated prices mortgages that weren't worth the paper they were printed on while they were turning around and selling the same garbage. It's bad enough to sell rubbish, it's even worse to buy, basically, the same rubbish (at inflated prices no less)! Many banks suckered regulators, rating agencies, and investors, but they (also) wound up suckering themselves. Now, lawyers will come and sucker them all.

I suppose there is a bit of a bright spot in this atmosphere of gloom (at least, if you're fortunate to work for them). There was one bank who 'got it' and didn't sucker themselves: Goldman Sachs. According to the above cited article and an earlier article in The New York Times -- Goldman Sachs Rakes In Profit in Credit Crisis (Nov. 19, 2007) -- 'Goldie' is the one I-bank that, as the article puts it, "made more money in the boom and, at least so far, has managed to keep making money through the bust."

How did they do it? One reason is that Goldman Sachs -- unlike so many of their competitors as well as hedge funds -- takes risk seriously. As a Merril Lynch (which is facing turmoil because they didn't do what Goldman Sachs did) analyst admits, “The risk controllers are taken very seriously ... They have a level of authority and power that is, on balance, equivalent to the people running the cash registers. It’s not as clear that that happens everywhere.” In fact, unusually, risk managers are given legitimate opportunities to make the kind of money that traders and corporate bankers make. That shows how seriously Goldie takes risk!

As one Goldie alumn put it, Goldman Sachs has a 'culture of success.' It's hard for people who talk about risk during booms (when the bubble is being created and inflated) to be taken seriously -- i.e., actually given authority to affect change. Goldman Sachs is one of the few places that -- against the grain -- has enough 'humility' (at least when it comes to the possibility of losing money ... but I suppose not when it comes to making it) to take the 'fearmongers' seriously and give them backing from upper management to affect change.

That's what happened: When they saw warning signs -- as early as 2006 (last year) -- that 'mortgage risk' was on the rise, they cut their positions and hedged their risks. The results: While their competitors were trying to dump toxic waste (along with valuable holdings that they had to sell below value to raise liquidity), Goldie's hedges were profitable.

Goldman Sachs is an example of how one can profit from being cautious and wary of Black Swan type risks. We all have to take risks. Life is, in many ways, like poker. But we have to know when to fold 'em and know when we shouldn't bluff ... or, at least, to not believe the bluffs.

(NB: Both Lisa Endlich & Emanuel Derman are Goldman Sachs alumni.)

The O.C. of the Arctic (or The Global Reach of the Credit Crunch)

2007-12-03T10:22:00.000Z

If anyone had any doubts -- or wishful thoughts (forlorn hopes) -- about how far the (mostly) American credit crises can reach, here is an article that should dispell any lingering doubts about how inter-connected financial markets are.

The New York Times has an article -- U.S. Credit Crisis Adds to Gloom in Norway (December 2, 2007) -- describing how Narvik -- a remote Norwegian town north of the Artic Circle -- has been harmed by investments in "complex securities investments" (i.e., credit derivatives). Here is a brief excerpt from the article:

Norway’s unlucky towns are the latest victims — and perhaps the least likely ones so far — of the credit crisis that began last summer in the American subprime mortgage market and has spread to the farthest reaches of the world, causing untold losses and sowing fears about the global economy.

Where all the bad debt ended up remains something of a mystery, but to those hit by the collateral damage, it hardly matters.

Tiny specks on the map, these Norwegian towns are links in a chain of misery that stretches from insolvent homeowners in California to the state treasury of Maine, and from regional banks in Germany to the mightiest names on Wall Street. Citigroup, among the hardest hit, created the investments bought by the towns through a Norwegian broker.

For Ms. Kuvaas, being in such company is no comfort. People here are angry and scared, fearing that the losses will hurt local services like kindergartens, nursing homes and cultural institutions. With Christmas only weeks away, Narvik has already missed a payroll for municipal workers.

Above all, the residents want to know how their close-knit community of 18,000 could have mortgaged its future — built on the revenue from a hydroelectric plant on a nearby fjord — by dabbling in what many view as the black arts of investment bankers in distant places.

“The people in City Hall were naïve and they were manipulated,” said Paal Droenen, who was buying fish at a market across the street from the mayor’s office. “The fund guys were telling them tales, like, ‘This could happen to you.’ It’s a catastrophe for a small town like this.”

Now, the towns are considering legal action against the Norwegian brokerage company, Terra Securities, that sold them the investments. They allege that they were duped by Terra’s brokers, who did not warn them that these types of securities were risky and subject to being cashed out, at a loss, if their market price fell below a certain level.

All of the familiar themes are there: relatively unsophisticated investors getting sold complex derivatives -- where these naivetes were the ones who were, in effect, 'writing' the derivatives ... i.e., they receive higher yields but expose themselves to tremendous losses (or as Nassim Nicholas Taleb so eloquently puts it, stepping in front of steamrollers to grab pennies), angry citizens that range from old age pensioners to kindergarteners, and threats of lawsuits. It happened with Orange County, California. While no one will mistake Narvik (in the winter) for 'the O.C.', the underlying problems are the same: unscrupulous derivatives salesmen and gullible, unsophisticated investors that get lured by higher yields without realizing that they are exposing themselves to Black Swan type risk.

Here is a bet I'm willing to make ... I'll bet that this sort of thing will happen again and again. Maybe next time it won't be credit derivatives or derivatives linked to municipal debt ... it'll probably be some other 'fancy' financial instrument ... but the same thing will happen again and again. The names and faces (and models) may change, but some things are constant: human greed, hubris, and gullibility.

Forecaster as Entrepreneur (or How Do You 'Know' Without Knowing)

2007-11-25T00:11:00.000Z

I came across a very interesting article in the Economics Focus feature of The Economist: A new fashion in modelling: What to do when you don't know everything (22 Nov. 2007). The article describes the work of NYU economist, Roman Frydman. In his new book, Imperfect Knowledge Economics, Prof. Frydman makes the case for using predictive models that are more intuitive and qualitative than those traditionally favored by economists.

As the article notes, Prof. Frydman starts from a very interesting proposition: "The forecaster is like an entrepreneur. He uses quantitative methods, but he also studies history, and relies on intuition and judgment." From this brilliantly crafted idea (and I am very sympathetic to this viewpoint), he crititques traditional methods of economic forecasting -- using exchange rates as a case study (of sorts). The method that comes under the most scrutiny is the dominant approach of the 'rational expectations' school. Much to -- what I can safely forecast -- the chagrin of the adherents of rational expectations, Prof. Frydman compares them to communist idealogues who insisted, to the bitter end, that communism could be made to work.

The problems with rational expectations -- which is so dominant in economics that even its critics essentially fall under its spell -- are legion and isn't worth detailing here. But there is one fact that best encapsulates its failings: Predictions of currency movements using rational expectations type approaches are usually worse than flipping a coin!

Someone who follows the bloodsport of the endless debates within economics and finance faculties between different schools of thought might think that Prof. Frydman might favor 'behavioural economics.' Surprisingly, although he does give behaviourialists credit when they critique rational expectations, Prof. Frydman is critical when behaviouralists turn around and try to 'precisely' forecast human behaviour (which, if you will recall, is what I call falling into the 'rational expectations trap.')

Prof. Frydman doesn't just cast stones; he offers solutions. What Roman Frydman proposes will be familiar to intellectually oriented traders -- mixing (or 'mashing,' as kids now a days would call it) quantitative methods with the spotting of qualitative regularities (or irregularities) that only a 'forecasting entrepreneur' (e.g., thinking traders and investors like George Soros, Warren Buffets, Nassim Nicholas Taleb, etc.) can do. Prof. Frydman's approach to uncertainty is essentially Bayesian as opposed to 'frequentist' -- i.e., it is inherently subjective. (See the latest book by financial theorist, Riccardo Rebonato: Plight of the Fortune Tellers: Why We Need to Manage Financial Risk Differently. In that book, Rebonato also advocates a Bayesian approach.)

The 'problem' with Prof. Frydman's -- and, I suppose, Riccardo Rebonato's or Nassim Nicholas Taleb's -- approaches are that the forecasting models that they are advocating will not be as 'precise' as the models advocated by the mainstream. My response to that: Good! What is the point of having precisely wrong models of reality (other than for falsification)? If we can get more accurate models of reality, we should be glad to sacrifice false precision.

In light of the recent credit crises, the closing comments in the article seem especially important:

Messrs Frydman and Goldberg are now turning their attention to the troubled subprime-mortgage markets, and the performance of the rating agencies. The rating agencies, argues Mr Frydman, have generally been better at rating corporate bonds than rating asset-backed collateralised-debt obligations. Why? One reason is that the rating agencies used both a mathematical model and the judgment of their in-house specialists when forecasting the default probabilities of corporate bonds; on subprime-related securities, they could only use mathematical models, not least because the instruments were so new. “They had no experience, no intuition, no entrepreneur,” he says. That is “empirical proof that relying on models alone is not wise.”

Finally Waking Up to the Credit Derivatives Mess

2007-11-10T12:54:00.000Z

Regulars to The Econophysics Blog know that, since day one of the current crises, I've been pointing out the role that credit derivatives have played in creating and worsening the credit/mortgage crises -- a fact that was obscured or under-reported by the mainstream financial press and 'experts.' There is an article in The Economist that basically confirms the case I've been making -- along with some new fears -- about the toxicity of credit derivatives: CDOh no!: With trades scarce and losses mounting, it is going to be a harsh winter (Nov. 8, 2007).

According to the very interesting and comprehensive article, the AAA tranches of CDOs (collaterised-debt obligations: a vehicle used to package credit derivatives) have been substantially downgraded in value (see the chart of the ABX index -- and index of credit derivatives -- below) with fears of more downgrades to come. This would wreak havoc on already shaky financial markets.

There is also the question of accounting for these credit derivatives. The recommended method is to stick it in a category called "Level 3" which assesses "fair value" using "assumptions that market participants would use." But is that a good way to assign "fair value"? This situation is made worse by the fact that Level 3 securities have grown so much that they "now exceed shareholder equity" of many banks. No wonder many investment and commercial banks (as well as insurers, hedge funds, etc.) have been accused of not marking down their credit derivatives sufficiently.

Things can get much worse: AAA rated securities are relied on by a diverse range of investors -- from old age pensioners and municipal goverments to high flying hedge funds and banks. If AAA rated securities take a bigger hit because of their links to credit derivatives -- and/or other type of credit linked instruments (linked to consumer loans, for example) start sliding -- things can get really ugly ... much uglier than it is now.

Book Review: The Mathematics of Natural Catastrophes

2007-11-04T17:34:00.000Z

I haven't written a pure book review blog post since coming to the UK, so I thought I would write one reviewing a book by a British author. Gordon Woo -- the author of The Mathematics of Natural Catastrophes -- was a senior wrangler in the Maths tripos as an undergraduate at Cambridge University. He went onto a PhD in theoretical physics at Cambridge as well (while taking a detour through MIT and Harvard). He is currently on the staff of RMS (a risk management consultancy) doing research on catastrophic risk and the risks of terrorism.

The title of Dr. Woo's book is slightly deceptive (but in a good way). Yes, it is literally about the mathematics of natural catastrophes, but it's a lot more than that. It is an insightful yet accessible guide to the philosophy of risk and chance.

Although the book has its share of mathematical formulae and equations, the book -- despite the title and the academic background of its author -- is less about maths (British English) in the colloquial sense (i.e., complicated symbolics) and more about maths in its true sense, a logical way of tackling problems. In that way, the book is highly readable and should be accessible to people with even rudimentary mathematical backgrounds, yet remaining sophisticated enough for people with more formal training in maths.

The types of natural disasters discussed in the book focuses on examples from geology and meteorology, but the discussion can easily be extended to other types of events (including terrorism). Not surprisingly, given Dr. Woo's background, the author applies the tools of mathematics, statistics, probability theory, physics, geology, meteorology, engineering, and actuarial methods, in order to get a grip on these thorny issues.

But he doesn't stop there; he also demonstrates -- in the framework of Isaiah Berlin's The Hedgehog and the Fox -- a certain intellectual 'foxiness.' Dr. Woo incorporates history, philosophy, and even literature into his analysis of catastrophic risk. For those interested in the increasingly important links between natural catastrophes and financial instruments, Dr. Woo devotes a chapter to financial issues (including Cat bonds) and other chapters to issues relevant to the insurance industry and the 'management' of extreme risk.

The most fascinating aspect of this book, beyond the purely practical (and there are definitely practical aspects to this book), are the philosophical aspects of the book. As a mathematician philosophizing about the nature of probability, Dr. Woo reminds me of another Cantabrigian mathematician (unfortunately, known more as an economist), John Maynard Keynes (especially in his magisterial, A Treatise on Probability). Dr. Woo's book has not received as much attention as Nassim Nicholas Taleb's Black Swan (my book review can be found here), but I strongly believe that fans of the Black Swan will enjoy reading The Mathematics of Natural Catastrophes.

Twilight of the Quants (or yet another reason for the current financial turmoil)

2007-10-27T02:29:00.000+01:00

Over the last few months, I've tried to offer some analysis about the recent market turmoil that I feel has not been fully understood by the financial press and so-called expert commentators (e.g., the role of credit derivatives in the current crisis). It turns out that there is another contributing factor to the recent turmoil in the markets: quantitative hedge funds.

The most recent Buttonwood column in The Economist (25 Oct. 2007), sheds light on how 'quants' have been adding risk to the market because of their strategies. These quant funds are staffed by mathematicians, physicists, etc., that are suppose to come up with ultra-sophisticated models that should, they promise, lead to higher returns. But the problem is that other funds also hire quants that use similar models. This leads to a kind of feeding frenzy (or a vicious cycle) where an increasing number of very smart people are chasing ever shrinking opportunities for genuine arbitrage profits, which causes them to either ratchet up risks and/or try ever more esoteric strategies (which are copied almost as soon as there is any profit to be made), which, in turn, lead them further down the slippery slope.

For that reason, as well as others, these funds -- just as recently foreclosed home owners and their subprime mortgage lenders (who, presumably, didn't do PhDs in maths, physics, or engineering) -- loaded up on leverage (either directly or indirectly via derivatives, etc.). When the markets turned against the quants, they tried to offload their now toxic investments (in credit derivatives, etc.). Of course they couldn't find buyers, so they had to unload more liquid and valuable investments in order to meet margin calls and/or stay in business. But all this did was to cause a stampede among quant funds to get rid of assets that they really shouldn't have gotten rid of but HAD TO because of margin calls, the need to delta hedge their positions, plain desperation, etc.

This is the story of so many financial bubbles bursting -- except on a high tech, post-modern level. This, according to Buttonwood, is what happened during August. It seems that no one on Wall Street or in the City has a memory beyond their last bonus. Didn't we go through this with LTCM? Program trading in October 1987? Yet we are told that ever more sophisticated models or ever faster execution of orders will lead to greater returns. But what these 'geniuses' don't realize is that the world doesn't always fit their 'sophisticated' models. Common sense should have told them that strategies and assets that weren't correlated before will become correlated once everyone else with a PhD in Computational Chemistry decides to sell similar things at the same time! The rules of the game are the same whether you are a down-on-your-luck homeowner or an over-educated quant.

But to be fair, quants shouldn't shoulder all the blame. Yes, it's true that, as the article points out, "instead of providing liquidity in a crisis, the quants added to the instability." But the same could be said for those who participated in the dotcom bubble, tulip-mania, the Roaring 20s, and a whole host of financial fads and fashions that went awry. The problem is not that we are too sophisticated or that we are not sophisticated enough; the problem is arrogance. The problem is being willfully blind to 'Black Swans.' I doubt that any amount of rigorous modelling, algorithmic trading, statistical arbitrage, or improvements in order executions will solve that problem.

Why some people won't stop teaching others how to lose money (or Still Getting Fooled by Randomness)

2007-10-15T00:55:00.000+01:00

Apologies for not updating more frequently. I have been trying to adjust to life in the U.K., so I haven't had much free time.

I wanted to put up a quick blog post about an interesting thing I experienced last week. I went to a presentation by a prominent finance academic (he holds posts in some top programs ... programmes in British English ... in finance, and has written a well known book about quantitative investing). He presented the results of a theoretical paper he wrote extending some of the standard neoclassical financial models in what I hoped would be interesting directions. Instead, this chap seemed to be making some of the same mistakes -- and, in some cases, introducing new errors into already flawed models -- that had been made before by some of the (unfortunately) leading figures in quantitative finance.

I politely asked him how his model related to the types of difficulties we have just faced (i.e., the credit crisis, real estate bubble bursting, Northern Rock, etc.) -- and his model, as advertised, should have had something of substance to say about it. Sadly, he and his cohorts (mildly) dismissed my musings. Their rationale was that their simplistic linear model couldn't cope with the non-linearity of the way real financial markets work (aside: actually, even based on linear type maths -- vector spaces, independence, etc. -- I and a few others doubted that the presenter's model was valid). Rhetorical questions: Isn't that the point? Why claim that you have a model of how financial markets should work when it doesn't and probably won't work that way?

I wanted to respond by saying something like: "Sorry for bringing in a dose of reality and spoiling the fun of building models of fantasy worlds." But, prudently, I didn't say anything of the sort.

But what this incident goes to show is that -- despite a cold slap to the face by the true nature of uncertainty (not continuous, but extremely discrete; not linear, but non-linear) by events that are barely a month old -- there are still people teaching finance to impressionable minds that refuse to incorporate some degree of humility and reality into a subject that can use quite a lot of both.

Game Theory and the Kyoto Protocol

2007-09-30T00:28:00.000+01:00

I thought I'd take a break from depressing news about the financial markets and tackle depressing news about the environment. I just read an article in the Economics Focus section of The Economist: Playing games with the planet, Sep 27, 2007. In that article, The Economist discusses research that analyzes the current impasse over the Kyoto Protocol from the perspective of Game Theory.

Basically, the Kyoto Protocol resembles the Prisoner's Dilemma -- a game where players should cooperate from the perspective of globally optimal payoffs, but the players have incentives that would cause them to defect from cooperation and lead to mutually harmful payoffs. The Prisoner's Dilemma can be ameliorated by converting it from its static form to a repeated game. In the repeated Prisoner's Dilemma, players can see what the other players did during previous rounds and 'punish' them for defection.

As Robert Axelrod (an American political scientist -- who took the science part seriously) and others have demonstrated, the best strategy that emerges for repeated PDs is the so-called 'tit-for-tat' strategy. In most cases, that strategy recommends that (a) players should start by cooperating, (b) if some subset of players defect, then they should be punished by the cooperating players but that this punishment should last no more than the time or magnitude required to get players back in line, and (c) hopefully, all players will return to cooperation.

Michael Liebreich, of New Energy Finance, argues that -- while the current impasse over Kyoto seems to be more like the static PD -- the situation should be seen as being more like the repeated PD. Mr. Liebreich offers hope that, with some alterations to the Kyoto and post-Kyoto attempts to control global warming, something akin to 'tit-for-tat' can bring about a global regulatory mechanism to combat global warming.

Although I admire Mr. Liebreich's no doubt good intentions, I think he is being too optimistic. The flaw with his thinking is that there is another framework to consider beyond Game Theory: externalities. As The Economist cheekily points out:

At any given summit on climate change, it is never long before some politician declares how “urgent” or “vital” or “imperative” it is to stop the planet from overheating. And yet few governments are willing to tackle the problem by themselves. In practice, what these impassioned speakers usually mean is that it is urgent—no, vital!—no, imperative!—for all countries but their own to get to grips with climate change.

This quote nicely sums up the problem with economic externalities (aka, external costs and benefits): The benefits of controlling global warming would be shared with countries not cooperating, but the costs will be borne only by those who cooperate. In other words, countries like the U.S. that refuse to cooperate with global warming treaties will free-ride off the countries that are doing something about global warming.

The logic of repeated PD and 'tit-for-tat' rests on the fact that, in those idealized scenarios, players can monitor defection and can adequately punish defectors. But with externalities, it would be difficult to monitor who benefits even though they are free-riding, and it would be even more difficult to punish free-riders without causing serious lasting damage to both the cooperators and defectors.

For example, let's say Denmark decides to punish America for not cooperating on Kyoto or Kyoto-like global warming control schemes. How would it do that? Dump toxic waste to get back at America? But that would cause lasting damage to not only America and Denmark but to the global environment itself ... precisely what they were trying to avoid!

Unlike 'tit-for-tat' of laboratory repeated Prisoner's Dilemma, in the real world global warming game, it would be hard to limit the punishment so that it would send a strong enough signal to cooperate but not so strong as to be destructive to everyone involved.

Back to the drawing board, I guess, for utilizing Game Theory for negotiating global warming treaties.

Northern Rock and Betting on Storms

2007-09-20T08:31:00.000+01:00

I apologize to regular readers of this blog for not updating for a while. The reason why I haven't updated is that I recently moved to the UK. I've been busy settling in so I haven't had time to update the blog.

The last couple of blogs I wrote were regarding the 'credit crunch' that was unfolding in America (where I just left a few weeks ago). It seems like trouble has followed me across the Atlantic, because Northern Rock -- a British mortgage bank -- has basically suffered a run on it in the last few days. The 'queue' (or, as we Americans call it, a line) outside the local branch of Northern Rock (it was actually more like a scrum) of depositors trying to pull their money out of Northern Rock reminded me of photos of similar scenes during the Great Depression. The BBC has adequate coverage of the situation.

As I've written before, so-called 'expert' commentators are missing the point about the 'credit crunch': The heart of the matter is that there are a bunch of credit derivatives contracts out there that are still toxic right now. I fail to see how even a large drop in rates by the Fed or the Bank of England priming the monetary pumps will solve the problem of derivatives run amok.

Speaking of derivatives and storms, Michael Lewis wrote an article for the New York Times Magazine a few weeks ago that talks about quants trading in catastrophe bonds: In Nature’s Casino (Aug. 26, 2007). You may recall I had a blog post about catastrophe bonds a while back. Michael Lewis is a great writer and I thought his article was very interesting and stimulating. Frankly, though, I wish John Seo would have stuck with math (or 'maths' in British English) rather than getting involved with derivatives trading. The article has a great quote from Dr. Seo's father when he chewed out his son for leaving academic science for Wall Street by saying, "The devil has come to you as a prostitute and has asked you to lie down with her." Apparently the senior Seo has Wall Street experience!

More on the Credit Crunch

2007-08-27T00:19:00.000+01:00

Hopefully, all of you have read my last blog post -- Credit Derivatives Meltdown & Book Review of 'Traders, Guns & Money' (Aug. 16, 2007). In that blog post (among other things), I outline a major factor in the credit crisis and market fall that is being ignored (or misunderstood) by most commentators -- credit derivatives.

I found several articles in the most recent New York Times that relate to the current crisis in the credit and real estate markets (and their knock-on effects to the financial markets in general). I don't think they get to the heart of the matter (credit derivatives), but they do talk about issues that are nonetheless important to any attempted explanation of what is going on now.

Drop Foreseen in Median Price of U.S. Homes by David Leonhardt and Vikas Bajaj (Aug. 26, 2007) : In the last few years, almost every real estate 'expert' dismissed the idea of a nationwide decline in housing prices across the U.S. Guess what? ... It's happening!

Inside the Countrywide Lending Spree by Gretchen Morgenson (Aug. 26, 2007): With many mortgage banks/lenders at deaths door (either closing down or dramatically reducing their mortgage lending operations), Countrywide's recent bailout from other banks ($11.5 billion credit line had to be drawn down 2 weeks ago and Bank of America recently took a 16% stake in Countrywide for $2 billion) is emblematic of the recent crisis in the credit and real estate markets.

A Psychology Lesson From the Markets by Robert J. Shiller (Aug. 26, 2007): Yale financial economist and author of Irrational Exuberance comments on what is happening in the most recent market crisis.

Will the Credit Crisis End the Activists’ Run? by Andrew Ross Sorkin (Aug. 26, 2007): Speculates that credit crisis will reduce the ammunition needed by activist hedge funds to ply their trade.

Just How Contagious Is That Hedge Fund? by Mark Hulbert (Aug. 26, 2007): Hulbert cites research by 3 financial economists (the most prominent being Rene Stulz of Ohio State University) arguing that hedge fund strategies may be correlated with each other. This is flies in the face of hedge funds' advertised goals of using strategies that are unique and distinct from one another. What this means is that if the strategies of a few hedge funds fail, then there is a good chance that others will fail as well. To some extent, we are seeing some of this with the credit derivatives bets made by some hedge funds.

Credit Derivatives Meltdown & Book Review of 'Traders, Guns & Money'

2007-08-16T20:47:00.001+01:00

Regulars to this blog may be familiar with my preference to not comment on contemporaneous events occurring in the markets. The basic reason for this is that I'd prefer to let the dust settle before I say anything about movements in the financial markets (if I have anything to say about it at all). I am making an exception to this general 'rule,' because the credit market meltdown that we are currently experiencing in the global financial markets just happens to coincide with a book review I wanted to write for a long time.

So what is this book I wanted to review that seems ironically (or, perhaps, appropriately) to be the perfect companion to the bursting of the credit/real estate bubble? The book I want to review today is titled Traders, Guns & Money (Knowns and Unknowns in the Dazzling World of Derivatives) written by financial derivatives expert and veteran trader, Satyajit Das.

The most succinct endorsement (obviously, I will give a more detailed endorsement below) I can give to this book is by comparing this book to two of the books -- Fooled By Randomness and The Black Swan -- written by one of my favorite authors, Nassim Nicholas Taleb. In a nutshell, Das' book takes many of the ideas developed and espoused in NNT's books and applies them, in a clinical and detailed (but accessible) way, to the world of financial derivatives.

But a stronger one-line endorsement of this book was given by Frank Partnoy (author of FIASCO: The Inside Story of a Wall Street Trader and Infectious Greed) : "When 'derivatives' and 'f******' appear together on every other page, you know someone has written the truth about financial innovation." (It's worth noting that Partnoy exaggerates the amount of profanity used in the book ... but his basic point is well put.)

In Traders, Guns & Money, Satyajit Das dissects and analyzes almost every aspect of the derivatives industry with the same level of skill and care as an expert crime scene investigator combs through the scene of a crime. No part of the derivatives world escapes the attention of Das. Sell side, buy side, over-the-counter (OTC) derivatives, risk (mis-)management, 'quants,' structured products, equity derivatives, credit derivatives (much more on this later), and even more exotic derivatives (like weather and carbon emission derivatives) are covered in this fascinating book.

Das uses several underlying themes or frameworks throughout this book. One of these themes/frameworks is his use of semi-fictionalized narrative -- presumably, based on his own long career in the derivatives industry -- to highlight the dark side(s) of the derivatives world. This is reminiscent of the style used in NNT's books (Das even has his own 'Nero'; although Das' Nero is more like NNT's Fat Tony ... in fact Das' Nero would make Fat Tony look like a debutante). Das' 'war stories' are salacious, but, more importantly, they serve the purpose of exposing the real world workings of the derivatives industry to naifs.

Another theme/framework Das employs throughout his book is a somewhat Popperian one: 'knowns' and 'unknowns.' Das categorizes the workings of financial derivatives into one of four categories based on permutations of knowns and unknowns. There are the 'known knowns' -- things that we know that we know and, thus, can have a high degree of certainty about. The second category is 'known unknowns' -- things that we don't know but we know that we don't know them; this adds a degree of uncertainty but it is manageable uncertainty (similar to NNT and Benoit Mandelbrot's "mild uncertainty").

The third category is rather fascinating to me when I first heard it: 'unknown knowns.' These are things that we know but we do not realize (or, many times, we don't want to realize) that we know it! This may sound far-fetched, but I think Das is correct to articulate this category. An example that Das cites to illustrate 'unknown knowns' is the idea of greed and fear that underlies the derivatives game. No matter what people may say (and even believe, to some extent) about derivatives as a tool to hedge risk, add liquidity to markets, etc., the almost unsaid truth is that the motivation behind trading derivatives is greed and the fear of missing out on greed. This is an 'unknown' known because the players have incentives to not admit this to others (or even to themselves) because it is, at the very least, impolitic to 'know' this known.

The last category are the 'unknown unknowns' -- the "things that you did not know you did not know" (p. 12). This is the most problematic category because the degree of uncertainty in this category is virtually unbounded. This is like NNT's "Black Swan" (or "wild randomness").

Lest one is tempted to think this is all idle philosophizing, as the book highlights along the way, both the 'unknown knowns' and 'unknown unknowns' seems to pervade the derivatives industry.

One of the 'unknown knowns' that Das book does a great job of exploring is the mythology of financial 'engineering.' Many business schools and economics departments would like to beatify quantitative finance by removing the messy realities of the real world and 'cleaning' (over-simplifying) it up so that it resembles something like civil engineering. Academic and industry naifs would like people to believe that Black-Scholes, Cox-Rubenstein, Miller-Modigliani, etc., turn derivatives valuation into something akin to bridge building (and, as the recent tragedy in Minnesota shows us, even bridge building is a lot messier in the real world than in textbooks).

Das does a lot to explode these myths. Yes, Das would concede, fancy quantitative models can help, but there are serious weaknesses with copulas, implied correlations, dynamic delta hedging, etc. In other words, model risk, basis risk (basically, comparing apples to oranges), marking-to-model or to a market when there is no liquid market for the instrument, liquidity risk and flight-to-quality, etc., will forever doom even the geekiest and 'greekiest' models to getting blind-sided by negative Black Swans.

Along the same lines is how Das' book exposes the dark underbelly of many derivatives contracts. Many (if not all) the textbooks and technical literature on derivatives seem to think that derivatives are created and structured by Mother Theresa's Sisters of Mercy. These other books/papers will describe vanilla call, put, forward/futures, swap contracts but will have next to nothing on 'exotic' derivatives, structured products, special purpose vehicles, credit derivatives, etc. Even books/papers that touch on OTC and exotic products tend to take an unrealistic and unworldly view of things; i.e., they seem to unskeptically accept the propaganda of sell side traders/derivatives salesmen that they are 'client-centric' and that they would 'never' try to hide anything or slip in financial equivalents of ticking time bombs into their derivatives products.

Fortunately, Das -- having been on both the buy and sell side of the business -- doesn't believe that derivatives salesmen and traders have taken a vow of chastity. Das exposes many of the hidden details in real world -- as opposed to the idealized models one sees in textbooks -- derivatives contracts/products. And, not surprisingly, these details show that derivatives aren't the seemingly innocent ways to make markets more 'efficient' as we've been led to believe. There is sketchy accounting, hidden leverage (often massive), outlandish terms, and other ugly and sordid details.

For example, one semi-fictional example of contractual shenanigans that Das gives is almost comical (if you have a mathematical bent) if billions of dollars weren't at stake. One swap contract would have had a near-bankrupt company pay $4 million a month to a dealer in exchange for the investment bank paying the company an amount based on the following formula/algorithm (adapted from pp. 10-11):

Max[0; $600 million * {7 * [(LIBOR^2 * 1/LIBOR) - (LIBOR^4 * LIBOR^-3)]} * days in the month/360]

If you know basic algebra, then you would realize that this term will always equal zero! [Hint: The LIBOR terms.]

There are many other aspects of this book that I can highlight and praise, but the remainder of this post will focus on the intersection between Das' book and the current turbulence in the markets: namely, credit derivatives. The current market meltdown -- as summarized in the current issue of The Economist -- revolves around collateralized debt obligations (CDOs), collateralized loan obligations (CLOs), and mortgage backed securities (MBS) [for the purposes of our discussion, we can consider all three to be virtually interchangeable]. It just so happens that Das' book contains the best overview of credit derivatives that I am aware of.

The problem that credit derivatives products are causing right now in the markets are complex and hard to describe in the limited space of this blog. However, I can very briefly outline the problems below:

(1) Credit derivatives, like CDOs, are causing problems right now, in part (again, it's much more complex than what I can get into at this point), because they are basically untradeable and unhedgeable at this point. Why? Because the assets underlying these credit derivatives -- for the most part real estate mortgages (but there are other kinds of debt, like corporate debt, at play here too) -- have tanked in value because of the rising levels of defaults and the increase in the (subjective) probability of defaults.

(2) That's not the only problem. The other problem is that investments in these credit derivatives vehicles/products are structured into what are called tranches. That is a fancy way of saying that different classes of investors in credit derivatives will get paid in different ways. The 'equity' and 'mezzanine note' holders are taking a bath on this freefall in the CDO 'market' (I use that term loosely, since much of this is OTC) since they had lower priority in cases where some of the holdings in the credit derivatives portfolio defaulted (i.e., they took the risk in return for the rewards, and the chickens have come home to roost). The catch here is that senior note holders who had the highest priority are also taking a beating. This came as a surprise to them (but, according to Das and to my way of thinking, maybe it shouldn't have been) because most of these CDOs are structured so that the senior notes will get the highest possible ratings by credit rating agencies -- AAA. Now, the senior note holders are finding that AAA might as well be FFF.

(3) To make matters even worse -- and this happens in virtually every market crash (bursting of asset pricing bubbles) -- investors, banks, etc., are compelled to sell assets in order to limit losses and/or hedge risk. The problem is that this is either hard to do and/or makes things even worse. Obviously, they want to get rid of non-performing and/or illiquid assets, but they can't right now (if ever) because they're heading toward worthlessness. So they have to sell off 'good' assets, which means that prices of assets that at first blush seems to have little to do with CDOs, MBSs, mortgages, lending, banking, etc., also fall precipitously. I.e., correlations are created when there was little or none before!

(4) To top it all of, there is a LOT of leverage involved (both explicit and implicit). Leverage makes downturns even worse. For example, the need to meet margin calls is what is causing the sell off that I described in point (3).

That's a nutshell description of what is happening now in the financial markets. Like I said, it is much more complicated than that I'm sure, but if you can follow what I just wrote, then you're probably more knowledgeable than the vast majority of the people who bought and sold CDOs over the years.

Getting back to Das and how his book relates to the current tremors in the markets ... Das' book is the only book that I'm aware of that gives an accessible account of the workings and structure of credit derivatives, including both financial and legal issues surrounding them. Chapter 9 of his book -- considering the mess we're in -- is well worth the price of the book in it of itself (although the rest of the book is just as great if not better)! I would go so far as to say that Das essentially predicted the current crisis over a year ago (the book was published last year, 2006).

The intersection between Das' book and the market meltdown brings us back to the theme of knowns and unknowns. Goldman Sachs has admitted that its hedge funds -- keep in mind that hedge funds have been big buyers of credit derivatives -- have been "hit by moves that its models suggested were 25 standard deviations away from normal" (from The Economist article). This is, in terms of standard Gaussian mathematical statistics, akin to saying that it was impossible for these losses to take place. Guess what ... the losses took place!

Apologists for hedge funds, investment banks, credit agencies, and investors may claim that these are what Das might call 'unknown unknowns.' How can anyone think that a (negative) 25 sigma event would take place? How can anyone know that credit rating agencies' grades are not worth the paper they're printed on when you need to count on them the most? Etc.

The problem with this line of argument is that these 'unknown unknowns' were actually known .. we just didn't want to admit that to ourselves. Nassim Nicholas Taleb, Benoit Mandelbrot, and -- as this blog post outlines -- Satyajit Das, have been warning us about these kinds of Black Swans for quite a while. Chance of a 25 sigma event taking place? Impossible from a 'normal,' bell curve perspective. Quite likely, from the Black Swan way of thinking.

The lesson we can learn from the NNTs and Das-es of the world -- those rare individuals who can combine sincere humility with the courage to face and embrace inconvenient truths -- are that the 'unknown unknowns' are really 'unknown knowns.' We actually know that 'impossible' events can take place because we should know that our pretentious models and heuristics are vulnerable to the messiness of the real world. The problem is that we don't know -- or, more accurately, we don't want to know -- that we know. That kind of self-knowledge is too painful to our ego, too inconvenient, and too humbling.

But ask yourself the question: Isn't it better to feed yourself humble pie rather than having it hurled at your head as is happening to so many traders and bankers now?

Catastrophe Bonds

2007-08-09T03:33:00.000+01:00

Catastrophe bonds -- or "cat" bonds -- are bonds (normally issued by insurance companies) that have high yields but lose their value when natural disasters (such as earthquakes, floods, hurricanes / typhoons, etc.) take place. In the past, the vast majority of cat bond investors were large institutional investors like pension funds and hedge funds. Recently, however, a mutual fund has allowed retail investors an 'opportunity' to gain exposure to this seemingly exotic alternative asset class.

The benefits of investing in cat bonds is that (a) it has yields that are substantially higher than most junk bonds and the sovereign debt of emerging countries, and (b) it (supposedly) has low correlation with other asset classes (of course, those touting cat bonds are tacitly assuming that natural catastrophes are not linked to market catastrophes). The problem is that these benefits come with a high price: Investors in cat bonds are implicitly writing (selling) options to insurance companies when they buy cat bonds.

If you know anything about financial options, you should know that the writers (sellers) of options -- which, counter-intuitively in this case, aren't the issuers of cat bonds, but the investors of cat bonds -- can lose their entire investment, and, in some cases, have virtually unlimited losses. If investments in cat bonds involve a lot of leverage -- which would not be surprising given that cat bonds are essentially another form of exotic financial derivatives -- then losses for investors can get quite ugly.

Cat bonds is another example of exotic derivatives and financial products that are finding their way to retail investors. Creators and marketers of these products are increasingly motivated to offer these products to the retail market because: (a) they have access to greater liquidity (thousands of 'little old ladies from Pasadena' can rival institutional investors when it comes to chasing liquidity), and (b) they provide a way to further (re-)distribute risk.

More on point (b) ... re-insurers -- who provide insurers with insurance against catastrophic risk -- are the obvious alternative to cat bonds. Unfortunately for insurance companies, re-insurers (and, for that matter, insurance companies) are like Mark Twain's proverbial bankers: "They give you an umbrella when it's sunny, but take it away when it's raining." In other words, re-insurance is plentiful when there aren't too many natural catastrophes, but they tend to dry up when it is most needed.

Cat bonds -- especially if retail investors get in on the act -- can be a way for insurance companies to obtain more 're-insurance' than they otherwise could. Unfortunately, for retail investors, these cats may not have nine lives when disaster strikes.

International Investing and China in the NBER Digest

2007-08-03T00:42:00.000+01:00

I came across a couple of interesting items in the July issue of the National Bureau of Economic Research's NBER Digest.

The first item that caught my eye was The Declining Gain from International Portfolio Diversification (by Les Picker). That article describes a NBER Working Paper by Karen Lewis, a financial economist at Wharton, where she examines the puzzle of why investors tend to disproportionately weight their investment portfolios to domestic securities and assets. This tendency is a 'puzzle' because this tendencymeans that investors forego the possible gains -- including lower correlated risks, higher returns from riskier foreign investments, etc. -- from international diversification.

Prof. Lewis finds that (a) international equity markets have become more correlated over the years (although she didn't find them to be as highly correlated as others have suspected them to be), and (b) foreign stocks that are listed on U.S. exchanges have become highly correlated with the U.S. market(s) over time. Thus, the potential gains from international portfolio diversification have been declining, and there seems to be relatively little to be gained in the way of diversification from investing in domestically listed foreign stocks.

The second item of interest in the NBER Digest is The Return to Capital in China (also by Les Picker). This article discusses research by professors Bai, Hsieh, and Qian, on what affects (if any) China's high investment rate (over 40% of GDP) has on returns to capital. The researchers found that (adjusted for various factors) China has relatively high returns to capital. It should be noted that this is an interesting finding because high investment rates can often mean lower returns to capital.

One of the plausible reasons why China's return to capital seems to be higher is -- despite misallocation of capital in many cases -- that China's economy has been moving rapidly toward more capital-intensive industries and techniques and away from purely labor-intensive industries of the past.

Derivatives, Leverage, and the Case of the Vanishing Bond Market Vigilantes

2007-07-27T00:09:00.000+01:00

A recent article in The Economist -- Vanishing vigilantes: Why the markets may be undermining central banks (July 19, 2007) -- points out that the so-called bond market "vigilantes" that used to punish central banks for being soft on inflation have gone awol. Bond yields have been low even for countries that have incurred large current account deficits.

One of the reasons offered by the article for this phenomena is that financial derivatives have allowed traders to take on greater leverage. This leverage has increased the prices of bonds (or assets linked to them) and that, conversely, means lower yields. This phenomena, along with the carry trade (where traders borrow in low-yielding currencies and invest in higher yielding ones), may have contributed to the case of the vanishing vigilantes.

Do Investors Have Too Much Information?

2007-07-18T09:51:00.000+01:00

A recent Buttonwood column (July 12) in The Economist magazine made the case for the idea that investors may have too much information to make good financial decisions. As the late, great Fischer Black pointed out, much of the 'information' -- whether they be news items, data, or even valuation models -- that is consumed by financial decision makers are essentially noise. As the article suggests, an increase in the amount of noise (in the guise of information) that investors are exposed to increases the level of confidence in their investment decisions. Unfortunately, this 'confidence' is over-confidence; various studies in the social sciences have pointed out that having more information does not correspond to improved performance in decision making and/or prediction of uncertain events.

This problem is referred to as 'noise trading' (I believe Fischer Black was one of the first finance intellectuals to rigorously study this idea). The ways investors try to 'solve' the problem of financial decision making in the midst of noise often lead to anomalies that are the bane of neoclassical financial economists (but are a boon to their 'behavioralist' brethren). For example, one study Buttonwood cites found that American mutual fund managers tended to favor investing in companies where senior officers went to the same universities as they did. Obviously, this is a silly and simplistic 'solution' to a complex problem, but silly and over-simplistic heuristics are what human beings often gravitate towards in the face of complexity.

Buttonwood suggests that a better solution to the problem of noise trading would be to exercise discipline in financial decision making. Rather than (over-)reacting to the latest bit of news on the financial wires, take the information (usually, noise) with a grain of salt and base decisions in a more equanimous manner. Sadly, this is easier said then done.

Success in Poker: How much of it is luck? How much of it is skill?

2007-07-04T07:24:00.000+01:00

Since the Main Event of the 2007 World Series of Poker is coming up in a matter of days, I found an article I came across in the July 2007 issue of Bluff magazine written by Aaron Brown and Brandon Adams that combined quantitative social science with poker to be extremely interesting. Aaron Brown, a financial trader and poker aficionado, has written a book about the intersection between poker and finance: The Poker Face of Wall Street. Brandon Adams has written a couple of books dealing with similar themes: Broke: A Poker Novel and The Story of Behavioral Finance.

What was interesting to me about their article, Luck and Skill in Poker, is that they came up with a way to quantify the extent to which luck (and skill) contribute to success in poker. They took the pre-tournament betting odds posted on Betfair.com of various professional poker players for the Main Event of the World Series of Poker. The authors used these odds to come up with implied probabilities of success (at least for the players whose odds were quoted on Betfair.com); in effect, they use Betfair.com and the odds it quotes as a predictive market. Using this probability function, they applied the Gini coefficient -- which is a concept usually used by economists to measure the inequality of income -- to the problem of how to measure the relative contributions of luck and skill to success in poker.

A Gini coefficient, as applied to poker rather than income, of zero would imply that poker is all luck. A Gini coefficient of one would imply that poker is all skill. The authors of the article found that the Gini coefficient applied to their method of assigning the probability of success to poker players is 24%. In other words, poker (at least by the authors' measure) is 24% skill and 76% luck.

From my personal experiences with poker, I think this split between three-quarters luck and one-quarter skill is about right (at least for no limit hold'em in large tournaments; other types of poker may have a larger skill component). As the article concludes about the Gini coefficient of poker, "It's far enough from zero to make skill obvious, but far enough from one to keep you humble ..."

Algorithmic Trading

2007-06-26T01:27:00.000+01:00

'Algorithmic trading' is trading done by computer programs (algorithms) that pick up on trade-worthy bits of information from streams of market data and financial news. According to a recent article in The Economist, algorithmic trading accounts for a third of share traded in the U.S. and analyst project that algorithmic trading in some form or fashion will grow to account for a majority of trading in the coming years.

One of the advantages to algorithmic trading is sheer speed. In trading, especially in 'statistical arbitrage,' even a few milliseconds can mean the difference between exploiting a profitable opportunity or missing it altogether.

There are problems with this type of trading. One of the problems is that the algorithms may mis-interpret data or not have enough or the right kinds of information to make the proper trading decision. For example, as the article points out, does "surprise" mean the price is going up or down? One solution to this is to make sure that algorithms properly combine pieces of information (e.g., matching "surprise" found in a news piece with relevant price data). Another solution is tagging the news items fed into the computers (but then how do you know whether the tags are correct?) -- which is being done by financial news providers like Dow Jones.

I believe that there are more profound and more troubling problems than those pointed out by the article. First, we might wind up seeing similar problems that we got with 'programed trading' (which is not necessarily the same as algorithmic trading) that contributed to the October 1987 crash that rocked the financial market; i.e., you can get massive herding effects since many algorithms (even if superficially different from one another) will often behave in similar ways to each other.

The second problem is that algorithmic trading is essentially data mining. Now, most people in the business world think that data mining is a good thing. In some cases, it can be on a practical level. But, to thinking mathematical statisticians, data mining is a highly dubious practice. As Nassim Taleb might put it, algorithmic trading might be mining data to confirm whatever 'white swans' that one hopes will provide trading profits. But what if a black swan happens? It's doubtful that trading algorithms can pick up on black swans any better than their human trading compatriots can.

A third problem -- which I won't elaborate on since there are mountains of books written on this subject -- are the ones faced by anyone working in artificial intelligence ... which algorithmic trading is sort of aiming at.

Thin Sliced Elections

2007-06-22T21:15:00.000+01:00

The NBER (National Bureau of Economic Research) Digest's latest issue (June 2007) has an article -- TV Appearance and Electoral Success -- that I found both fascinating and disturbing at the same time. In their paper, Thin-Slice Forecasts of Gubernatorial Elections, Daniel Benjamin and Jesse Shapiro, conducted an experiment on a group of Harvard students to see whether or not the physical appearance of political candidates alone could lead to correct predictions of the outcome of elections. These subjects were shown 10 second clips of televised debates of candidates for governors in several U.S. states. Some subjects were shown clips without sound while others were either shown clips with muddled sounds or with full audio.

The researchers found that those who saw silent videos had greater success at predicting who would win the elections (58% of picks actually won their elections) compared to most other factors used to make electoral predictions. The students who made their predictions after seeing the videos either with muddled or full sounds could do no better than had they randomly guessed who would win (ranging from 52 to 48% success rates). Furthermore, purely visual forecasts were considerably more accurate than electoral predictions based on other measures such as per capita income, unemployment rates, and state fiscal health.

The results of this research is consistent with similar experiments carried out on subjects outside the U.S. to find out what factors people actually used when picking their political leaders. For example, two studies carried out in Europe (Romania and Finland) found that subjects basing predictions based on physical appearance tended to do better than those who had based their predictions on other seemingly more 'politically correct' factors such as competence in economic and policy matters.

Contrary to expectations, adding policy information to the predictive mix seems to worsen the chances of making correct predictions. The findings of this body of research may explain why 'experts', "who are highly informed about and attentive to policy matters, are often found to perform no better than chance in predicting elections" (and, frankly, experts often do worse than chance in making predictions and this mis-predictive 'ability' is applicable to other fields as well).

These findings are consistent with the idea of 'thin-slicing' which was popularized by journalist, Malcolm Gladwell, in his best-selling book, Blink. Malcolm Gladwell's contention is that making rapid, intuitive decisions are often not much worse than -- and may often be superior to -- making more deliberate decisions. Although I really admire Malcolm Gladwell and, to some extent, agree with this idea, this is the part that I (and I'm sure others) find somewhat disturbing. As I recently wrote up in a blog post on the Travelers' Dilemma, those who make snap decisions tend to make more emotional or random rather than rational or strategic decisions. Thus, while in a positivist sense 'thin-slicing' may be the method used to make decisions in political elections (and in other situations), in a normative sense this type of decision-making is a recipe for choosing incompetent and disastrous leaders.

Benjamin and Shapiro's research seems to contradict econometric models of elections done by researchers like Ray Fair, who found that economic and other policy factors can play significant roles in making electoral predictions. Having said that, all three economists agree that incumbency is the factor with the most predictive power in trying to forecast electoral results. (Campaign spending is another factor that has great predictive power.)

The research discussed in the NBER Digest both complements and contradicts research carried out by Philip Tetlock, a political scientist at U.C. Berkeley. Prof. Tetlock -- most recently in his book, Expert Political Judgment: How Good Is It? How Can We Know? -- eloquently debunks the predictive 'abilities' of experts. Tetlock's research seems consistent and complementary to Benjamin and Shapiro's findings in that all three would agree that experts are bad at making predictions. Tetlock's research is at odds with the reasoning laid out in the Digest in that Tetlock, as Isaiah Berlin would have put it, believes that 'foxes' -- those who are intellectually curious and have wide-ranging interests (i.e., knows at least a little about a lot of things) -- tend to do better than 'hedgehogs' -- those who are focused on a few matters (i.e., knows (a little? a lot?) about a few things ... usually one thing) -- in making predictions. Benjamin, Shapiro, et al., seem to suggest that such a distinction may not matter at all -- i.e., it really doesn't matter whether or not an expert is Berlin's intellectual fox; in fact, narrow-minded hedgehogs -- so long as they are focused on the right 'few' things (such as visual cues of personal appeal in this case) -- may make better predictions than Tetlock's foxes.

Perhaps the most fascinating aspect of Benjamin and Shapiro's findings -- beyond how the electorate is susceptible to making snap decisions based on 'looks' -- is the complexity of how people thin-slice during elections. Although the experimental subjects did predict better with purely visual cues (without sound or policy information), these visual-based predictions do not seem to be simplistically correlated to factors that are obviously associated with physical attractiveness.

Instead, there seems to be a sense of some intangible quality -- we can call it 'charisma' -- that somehow can be picked up visually (and perhaps is muddied a bit when we start considering the substance of what the candidates have to say) that seem to be the key factor in the predictive success of those who based their decisions on silent videos. Thus, personal charisma of a candidate -- as vague a concept as that may seem -- is a superior to the predictive power (or lack thereof) of more concrete factors like policy matters and competence.

As Benjamin and Shapiro aptly conclude, "Adding policy information to the video clips by turning on the sound tends, if anything, to worsen participants' accuracy, suggesting that naïveté may be an asset in some forecasting tasks."

eBay 'Sniping' and the Power Law

2007-06-16T00:26:00.000+01:00

'Sniping' -- where a bidder waits until the last moments of an auction to place a bid -- is a tactic used by some eBay auction aficionados to gain an upper hand in bidding for an item.

According to an article (June 23, 2006) in the New Scientist, two South Korean physicists, Byungnam Kahng and Inchang Yang, found that a power law equation explained the observed patterns in eBay auction bidding. The power law reflects the fact that most of the bidding for items tend to take place near the end of an auction. Thus, according to their article in Physical Review E (vol. 73, p 067101, 2006), 'sniping' is a rational strategy to employ in eBay bidding.

This research builds on the work of experimental economist / game theorist, Alvin Roth. His article in the American Economic Review (vol 92, p 1093, 2002) came to similar conclusions.

Traveler's Dilemma: 'Irrational' Game Theory

2007-06-07T11:11:00.000+01:00

I just read an interesting article in Scientific American on game theory -- The Traveler's Dilemma (June 2007) -- written by Kaushik Basu, the economist who created the aforementioned game paradigm. The Traveler's Dilemma, as the Sci Am article describes it, is very similar to the Prisoner's Dilemma except that the payoff matrix of the typical PD scenario is a kind of subset of the payoff matrx of TD (specifically, when the players are restricted to the lowest two strategic choices, TD is equivalent to PD).

The Traveler's Dilemma (TD) basically involves the following scenario: Two players can individually choose a figure (usually couched in terms of some monetary amount or price) without in any way conferring or coordinating with each other. If both players choose the same amount, then they will each be paid that amount (hence, like Prisoner's Dilemma (PD), there are meta-incentives to 'cooperate'). But if they choose different amounts, then the player who chooses the lower amount will get that amount plus some reward/bonus while the player who chooses the higher amount will get the lower amount minus a penalty (which is usually the same size as the reward). Thus, as in the better known PD, the TD's payoff structure provides myopic incentives for players to 'defect' and try to undercut one another.

Under the standard assumptions of 'rationality' (I put it in quotes here because I find economists' and game theorists' definition of rationality to be too straight-jacketed and narrow) and the logic of backward induction (a solution concept in game theory), the players in TD should defect and choose the lowest number possible (similar to the result in PD). Of course, this result is to the deteriment of both players since both of them would have gotten a higher payoff if they had 'cooperated' and chosen a high amount.

Prof. Basu argues -- providing ample experimental/empirical evidence and common sense observations -- that, in reality, the theoretical result of TD does not hold. In practice, most players who participate in TD inspired game theoretical experiments tend to choose figures in the high range of options. These empirical results fly in the face of the standard assumptions of 'rationality' (although, as Prof. Basu helpfully points out, it is consistent with a sort of meta-rationality) in game theory and economics.

The article makes some other interesting observations. One of them are the results of an experiment carried out by economist/game theorist, Ariel Rubinstein. Rubinstein found that people who based their decisions in Traveler's Dilemma style experimental games using strategic reasoning or more formal 'rationality' took the longest time to respond to prompts. Conversely, those who made decisions on spontaneous 'emotional' or untrained intuitive responses or who made "random" (i.e., inexplicable or perhaps even crazy) choices tended to take the least amount of time in making decisions.

Another interesting observation made in the Scientific American article is whether or not the economist's/game theorist's concept of rationality needs to be modified and expanded. Prof. Basu argues that the standard notions of rationality are inadequate to explain the empirical tests of the Traveler's Dilemma as well as the Prisoner's Dilemma (especially, iterated PD). The problem that the article zeros in on is the assumption that rationality is "common knowledge" in its philsophical, formal logic sense of that term (i.e., that each of the players in TD know that the other player will act 'rationally' and they are each know that the other knows). Prof. Basu argues that people may not always conform to this standard assumption, especially in repeated games such as iterated (or repeated) Prisoner's Dilemma.

As the article points out, perhaps these observations from empirical tests of TD and PD will lead to a rethink of game theoretic logic. Perhaps there is a "meta-rational" consideration(s) that lead people to (without direct collusion and communcation) choose mutually beneficial options. This type of reasoning should give us some reasons to hope in humanity at large.

Timber! Money Can Grow on Trees

2007-06-01T08:01:00.000+01:00

A few years ago, I came across an alternative asset class that institutional investors -- especially university endowments -- that struck me as being really out-of-the-box: timberland. At the time, I asked myself, "Why are sophisticated investors investing in trees and forests?"

A recent New York Times article, For Some Investors, Money Grows on Trees (May 27, 2007), answered many of the questions I had about this alternative investment. In a nutshell, investors are counting on revenues from sales of timberland products to lumber, paper, and other companies, along with potential gains from the underlying real estate. Rather than investing in individual lots (which would make little sense for large institutional investors like pension funds and university endowments), investors invest through TIMOs (timber investment management organizations) and timber REITs (real estate investment trusts).

Historically, investing in timber has done well. An index of returns on timberland investments since 1986 (when the index was created) to the first quarter of this year rose at an annualized rate of 15.09%. In the last three years, the return was 14.63%, which is higher than the returns on the S&P 500 over that period (12.25%).

The most appealing aspect of this asset class is that it has had low correlation with the performance of stocks and bonds. 'Low correlation' is important to risk management under conventional financial economics portfolio theory. I should note that that I am usually highly skeptical and suspicious of claims of 'low correlation' between asset classes and markets since 'correlations' are (a) dynamic, and (b) there might be less obvious links between investments that simple measures of correlation don't pick up. However, in this case, this idea does seem to pan out at this point in time.

Note: The best books I'm aware of dealing with the role that alternative assets can play in managing an investment portfolio are the two books written (thus far) by David Swensen. I'm not sure if Yale's endowment invests in timberland, but I would be shocked if they didn't. I am aware of other university endowments that do invest in timberland, e.g., Caltech.

Greenspan chimes in on Chinese stockmarkets

2007-05-28T22:35:00.000+01:00

I've written a couple of posts lately about the possibilities of a stockmarket bubble in China (More signs of a Chinese stockmarket bubble, 5/13/07, and Makings of a Chinese Stockmarket Bubble?, 4/29/07) . According to the New York Times (5/25/07), former Fed Chairman Alan Greenspan has chimed in as well. According to the Time article:

Mr. Greenspan, now 81, struggled to contain the tech stock boom, issuing his famous “irrational exuberance” warning in December 1996 only to watch the American market keep rising and finally collapse in early 2000. He tried his hand at forecasting Chinese stocks on Wednesday, telling an audience in Madrid by satellite that the Chinese market was “clearly unsustainable” and could undergo a “dramatic contraction.”

After setting records on Monday, Tuesday and Wednesday, the A shares, those traded in yuan, fell 0.47 percent in Shanghai and 0.6 percent in Shenzhen on Thursday as investors responded to the warning.

But the warning was not news to Mr. Zhou and other Chinese officials. The central bank, securities regulators and prominent business executives have all been cautioning investors that buying stocks is not a guaranteed path to riches — all with less apparent effect than Mr. Greenspan.

To reiterate my earlier warnings, developments in China can (and has) effects on an increasingly inter-linked, globalized financial markets.

Book Review: Chaos Theory Tamed

2007-05-22T02:30:00.000+01:00

I'm presuming that most of you have either read my musings (The Black Swan ... "Well That's Life!") on Nassim Nicholas Taleb's new book, The Black Swan, and/or read the book on your own accord. It occurred to me that a large segment of the reading public may have difficulty following the mathematics presented in Part Three and in the Notes of Nassim Taleb's book. If your mathematical skills or training is limited or rusty, then you will certainly have a hard time following the logic of the Black Swan, fractal randomness, power law, etc. Even if you have had a fair amount of technical education, many of the topics covered in The Black Swan aren't things that are normally covered in the standard curriculum.

Fortunately, there is a (partial) solution to this problem. Chaos Theory Tamed, by Garnett P. Williams, clearly explains much (but not all) of the mathematics invoked in The Black Swan: the mathematics of complexity theory. (Note: There are epistemological distinctions between complexity theory, chaos theory, fractals, etc. However, for the purposes of this book review, I will mostly ignore those distinctions. At any rate, Garnett Williams' book covers math that are cross-disciplinary and would be useful for any of those aforementioned categories.) Uniquely, Garnett Williams' book manages to explain the mathematics of complexity, chaos, and (to some extent) fractals in a way that is both accessible yet sophisticated.

Most books on chaos theory, complexity theory, fractals, etc., fall into two categories. The first category are books that are of a 'pop science' / 'pop math' variety; relatively easy to understand but whatever knowledge one can glean from these books are given with a lot of hand-waving and not a lot of ways for more sophisticated readers to get beyond generalities and the 'gee whiz' factor. The second category of books are for the more technically minded. The more technical books are (hopefully) good for the initiated but are over the heads of the uninitiated. Frankly, even for those comfortable with the mathematics and scientific jargon invoked by these technical works, the more formal papers and books are usually unpleasant to read and may deny people the sense of epiphany that one should get from good science.

There are a handful of books that attempt to bridge this gap between pop sci/math and more formal literature, but most of these books, frankly, fail. Garnett William's book is the one bright exception ... a positive Black Swan.

The mathematical prerequisites for reading Chaos Theory Tamed are light. The reader only needs to have the equivalent of a good American high school math education (basic algebra, and hopefully, some exposure to pre-calculus), and the patience to go through the logic (and equations) presented throughout the book. Unlike the few other gap bridging books that are in the marketplace, Chaos Theory Tamed's mathematical prerequisites are very minimal.

This low level of mathematical pre-knowledge should not be mistaken with a low level of mathematical sophistication. On the contrary, Garnett Williams' book does a great job of covering math that is actually invoked and used by professional researchers in the fields of chaos and complexity theories (as opposed to hand-waving toy models presented in other pop sci/math books and, even, in the gap bridging books on chaos theory). Without assuming an active knolwedge of calculus, Garnett Williams explains the workings of difference equations and differential equations of the type that Edward Lorenz and Mitchell Feigenbaum used to 'discover' chaos theory. Like other books on chaos theory, Chaos Theory Tamed discusses topics like 'strange attractors','bifurcation,' etc.; unlike those other books, Garnett Williams actually explains what those terms mean and the logic (math) behind them.

More relevant to Nassim Taleb's The Black Swan, Chaos Theory Tamed does an excellent job of explaining probability theory and the mathematics of the power law.

Garnett Williams does an excellent job of explaining the nuts and bolts of probability theory and mathematical statistics to the uninitiated. In fact, if that is all he did in his book (and he did much more than that), it would be a worthy book in it of itself since he provides the sort of explanations that would be useful to anyone wanting to learn probability and statistics beyond an elementary level. He also explains information theory along with the idea of entropy (in both the thermodynamics and Shannon information theory senses) and ties those ideas in with probability theory. Again, Garnett Williams' explanation of these complex topics -- topics that are so riddled with difficulties that more technical books try to avoid it -- are both so ambitious and helpful to the uninitiated that I could recommend the book on these grounds alone.

But Chaos Theory Tamed doesn't stop with explanations of 'strange attractors,' 'entropy,' and 'autocorrelation in time series.' Garnett Williams' book gives the best accessible explanation of power laws that I've encountered. Chaos Theory Tamed explains power law and scalability (scale free, scale invariant, etc.) in terms of 'dimensions.' Dimensions are essentially the kind of dimensions that we are all familiar with ... three dimensions of space (four dimensions if you include time), two dimensions of a sheet of paper or a fictional 'flatland,' and the single dimension of a Platonic straight line. With power laws, the dimension of what is being measured is the exponent and is relatively invariant (within some range). When graphed on log-log axes, a power law is a straight line and the power law exponent (represented as 'alpha' in The Black Swan) is the slope (usually, negative) of this line.

Garnett Williams uses the concepts of dimensions and scales in order to give a very clear-headed explanation of fractals. Chaos Theory Tamed doesn't dwell on fractals as much as other books that are more specifically focused on fractals, but, when the book does deal with fractals, the explanations of what fractals are and how they relate to chaos theory are brilliant for its clarity. Basically, fractals are defined in this book as being "fractional dimensions" -- i.e., instead of 1, 2, or 3 dimensions (integer dimensions), fractals are fractional (non-integer) dimensions (1.2, 1.4, 2.8, etc.). I actually find this sort of definition to be much more useful and interesting then the thousands of pretty pictures of fractals I have seen in other books, magazines, and on the web.

One can tie this fractal dimension idea in with power laws in the following way: The power law exponent (the dimension) is usually not a whole number. For example, 1.1 is the exponent (as provided by Nassim Taleb in The Black Swan, p. 264) for the net worth of Americans; that power law exponent translates to the top 20% of the wealthiest Americans having 86% of the wealth (from p. 265 of The Black Swan). Again, this way of thinking about fractals is at least as valuable as seeing a pretty picture of fractals.

Another distinguishing feature of Chaos Theory Tamed is that, unlike other books on chaos theory, it goes into how one might empirically detect and measure chaos and/or complexity; i.e., it goes beyond mere scientific speculation or even theorizing. The concept of dimensions (i.e., the power law exponent; the 'alpha' in The Black Swan) is important to the empirical study of chaos and complexity. There are different standards/measures of dimensionality including Hausdorff dimension, information dimension, and correlation dimension; they are distinct but similar ways of measuring dimensions. Information theory, in the form of Kolmogorov-Sinai entropy and mutual information, is also important to the quantitative study of chaos, and Garnett Williams does a commendable job of explicating these topics.

Garnett Williams is also quite frank about the limitations and difficulties inherent in trying to empirically detect and measure complexity. This note of caution fits in well with Nassim Taleb's warnings about not placing too much weight on 'precise' (frankly, there aren't any) measures of 'alpha' when thinking about randomness from a Mandelbrotian perspective.

One final point to praise in Chaos Theory Tamed is its glossary. Its glossary -- clearly defining terms in chaos theory, probability, mathematical statistics, information theory, etc. -- alone is worth the price of the book!

Garnett Williams' professional background is worth noting. He was a geologist for the U.S. Geological Survey. A geologist might not be the first person to come to mind in writing a book about the mathematical backbone of chaos theory, but in many ways he is the ideal person to write the book. The distribution of earthquakes and other natural geological phenomena follow power laws and have been studied by complexity theorists as being examples of complexity in nature. In fact, many natural -- as opposed to social -- phenomena seem to be consistent with Black Swan theory. Thus, Nassim Taleb's ideas should not be thought of as being confined to social sciences only but as being applicable to natural sciences as well.

Bottom-line: If you're looking for a clear-headed explanation, that is both accessible and sophisticated, of the mathematics behind The Black Swan (and complexity/chaos/fractal theory, in general), then Chaos Theory Tamed is a great place to start ... in fact, it's the best place to start. Frankly, I wish there were more books like Chaos Theory Tamed and more authors like Garnett Williams; books that aren't afraid to cater to the intellectually ambitious and science/math writers who aren't afraid to lay bear the equations that tend to mystify science and math to the uninitiated.

The Foresight Saga Revisited (or How Much Money Can You Make If You Had Perfect Foresight?)

2007-05-16T09:03:00.000+01:00

So what is the 'Foresight Saga'? The Foresight Saga was a gedanken (i.e., thought experiment) conducted by The Economist magazine in its fin de siecle (1999) Christmas issue. The Economist magazine created an imaginary character named 'Felicity Foresight' who was able to perfectly predict the performance of financial markets -- across different asset classes and across borders -- for each and every upcoming year from January 1st 1900 onwards.

Starting with an initial investment of $1 in January 1st 1900 (and by reinvesting any dividends and/or interest income in the coming years), Felicity Foresight would decide at the beginning of each year which investment would bring the highest return (capital gain plus income) for that year and put all her wealth into that single asset. She would repeat this process year after year, shifting her funds to match her new forecast for each and every year starting from the year 1900.

How did Felicity do? By January 1st 2000, she managed to turn $1 into $1.3 quadrillion even after deducting transaction costs and taxes. Compared to the $9,000 she would have earned had the $1 been invested in a broad collection of American stocks, Felicity Foresight's performance is truly staggering! The last time The Economist checked in on Ms. Foresight (January 2, 2003), her investment acumen more than doubled her portfolio (to $2.7 quadrillion). [Note: All figures in this paragraph are the revised figures from the 2003 article, and not from the original 1999 article.]

In addition to Felicity Foresight, the Foresight Saga also included two ancillary characters (and potential suitors) -- Henry Hindsight and Charlie Contrarian -- that added zest to this tale of predictive perfection. Unlike Felicity, neither Henry nor Charlie were able to perfectly foretell the future direction of financial markets.

Henry Hindsight follows the same investment process that Felicity does with one major exception: Henry invests in the previous year's best performing asset. In other words, Henry Hindsight is like most investors, following 'fashions' and 'trends.' Henry's initial $1 invested at the beginning of 1900 would have only grown to $783 -- much less than either Felicity's portfolio or investing in a broad index of American shares.

Charlie Contrarian, on the other hand, invested in the previous year's worst performing asset (apparently believing in a sort of 'mean reversion'). Charlie did somewhat better than Henry -- turning his $1 into $1,730 in a century of investing -- but not as well as either Felicity or a broad index of U.S. equity.

The following chart lists the investment choices that Felicity Foresight made over the last century (you can click on the image to enlarge it).

Needless to say, no one has perfect foresight. So inventing 'Felicity Foresight' may, at first blush, seem a rather pointless exercise. However, I believe that we can learn a great deal from gedankens / empirical studies like the Foresight Saga.

One of the things we can learn from this thought experiment is that financial experts often underestimate the effects of taxes and transaction costs. If Felicity's porfolio had been constructed without those costs, it would have grown to $27.5 quintillion; i.e., 99.99% of potential investment wealth was eliminated by transaction costs and taxes (along with effects of compounding). Many experts tend to think of these kinds of costs to be negligible and readily dismiss them, but this extreme example demonstrates that investment costs can add up -- or, more precisely, compound -- to a sizable amount in the long run.

Another valuable lesson that can be learned from this seemingly fanciful tale is that there has been a fundamental change in the ability to achieve investment performance over the last decade and a half. Until the early 1990s, both Henry Hindsight's and Charlie Contrarian's strategies -- which are the typical strategies used by most investors -- would have led to respectable gains. Since then (or at least until the early 2000s), these strategies would have been less successful and, up until the year 2000 or so, would have led to substantial losses.

What is the nature of this 'fundamental change' over the last decade and a half or so? Could it be a more globalized financial market where poor performance in one part of the globe or in one asset class can reverberate much more readily than prior to the 1990s? Could it be that a more dynamic marketplace has shortened the time frame and/or reduced the opportunities where either of the two traditional investing strategies can profit?

One final lesson that can be learned from the Foresight Saga is that the creator(s) of the story have shown that they -- unlike Felicity, but like the rest of us -- lack perfect foresight. None of the installments of the Foresight Saga (the last one was in January 2003) foresaw with any detail what has happened since then and no one could have profited at the rate that Felicity did by what they could glean from her tale of investment success.

Despite the lack of useful predictions for the future, I do hope that The Economist revives the Foresight Sage in the near future because of the insight that this gedanken gives us about the past's future. What do I mean by the 'past's future'? What I mean by that is that we can use the Foresight Saga -- not as a way to give us perfect foresight (which it doesn't) -- but as a way to put ourselves in the proverbial shoes of those who in the past had been trying to make decisions based on uncertain projections of the future. In other words, we can evaluate the past's predictions about the future ... and see the frustrating nature of such attempts at prediction. For example, anyone who had predicted in 1939 (the eve of World War II) that, by the early 1940s (well into World War II), the French stockmarket would have over a 200% annualized return would have been dismissed as a lunatic ... yet it happened!

The Foresight Saga is more about hindsight than foresight ... gendankens and empirical studies like this one can place us back in time to see how those who came before us (or even ourselves in the distant past, if we are old enought) viewed their future ... and usually got it wrong! The most important lesson to learn from Felicity Foresight's amazing track record as an investor is how all of us, in reality, lack such consistently perfect foresight about our future.

More signs of a Chinese stockmarket bubble

2007-05-13T08:01:00.000+01:00

According to the Financial Times [in Bourses in China eclipse all of Asia (May 9, 2007)]: "The value of shares traded on China’s stock markets on Wednesday was greater than the rest of Asia combined – including Japan – helping the benchmark index to breach the 4,000 mark for the first time. Analysts said this was almost certainly the first time that turnover at the Chinese bourses had exceeded that of the rest of Asia." (Although, it should be noted, that the Chinese stockmarkets in Shanghai and Shenzhen are still substantially smaller than the markets in Japan, the UK, and the US, in terms of market capitalisation.)

This is more evidence for some of the comments I made in previous posts on China's financial sector ... the latest post being Makings of a Chinese Stockmarket Bubble? (April 29, 2007). A financial bubble (that bursts ... as they invariably do) in China could have devastating consequences for markets (and economies) of other countries (including the US, the UK, and Europe). It's definitely worth keeping an eye on developments in China.

Switching Costs

2007-05-10T19:40:00.000+01:00

In his weekly Financial Times column, 'The Undercover Economist,' Tim Hartford wrote about research into the costs of switching goods and services (April 27, 2007). One might expect (especially with the 'rational man' presumption of most economists) that people would make the switch away from goods and services they have been accustomed to unfamiliar goods and services in order to save money. The research and examples Tim Hartford cites, however, contradicts this: People often lose money by making switches.

Why? There are many possible reasons for this. One possible reason is that searching for alternatives is itself costly. But this rationale doesn't seem to apply here since the article talks about scenarios where people searched for alternatives, made the conscious decision to switch, and, yet, it still costs them more than if they had stayed with their prior commitments.

The better explanation for higher switching costs (under these circumstances) is a combination of information asymmetry and just plain confusion about the true costs of making the switch. One of the examples the article cites is switching electricity suppliers. Consumers get confused about the different tariffs and pricing schemes involved in switching utilities suppliers. Another example the article cites is hedge funds. Investors have a hard time figuring out whether a particular group of hedge fund managers are good or not. The information asymmetry can come in because suppliers -- whether they supply electricity or hedge fund investment management -- can 'exploit' this confusion or lack of information/knowledge on the part of consumers.

All of this turns on its head the usual presumption in economics that prices efficiently reflect all available (and, in the most strongest forms, even all or most private) information. So, even assuming that consumers are acting rationally, prices don't seem to serve as an efficient means of delivering information and making 'rational' economic decisions. This suggest a sort of 'shadow' or 'undercover' prices; perhaps, it takes an Undercover Economist to point that out.

The Black Swan ... "Well, That's Life!"

2007-05-04T07:37:00.000+01:00

The late, great Polish journalist, Ryszard Kapuscinski, wrote -- in his book on the last days of the Soviet Union, Imperium -- that the genius of the Russian people can be summed up in their oft-repeated phrase, "Well, that's life!"

A young boy finds that his hometown is no longer a part of Poland but is, instead, a part of the Soviet Union due to the extremely improbable (and brief) courtship between Hitler and Stalin. Well, that's life! Shortly thereafter, that same boy finds many of his friends and neighbors being carted off on trains to Siberia by the NKVD (the forerunner to the KGB) for no apparent reason. Well, that's life!

On some perverse whim, Stalin decides to (literally) starve ten million Ukrainian peasants -- almost a third of the population -- to death. Well, that's life! At the death/work colony of Kolyma -- a place that gave birth to another phrase of relativist consolation, "Don't despair, it was worse in Kolyma!" -- Beria's henchmen gave their victims the 'choice' between dying of hunger, hard labor, sleep deprivation, disease, sadism, hopeless despair, (literal) freezing, and, for the fortunate few, being shot. Well, that's life!

All of a sudden, the mighty Soviet Union -- which had terrorized, humiliated, enslaved, and froze people to death -- collapses and disappears from the maps ... its red tzars going the way of the tzars of old. Well, that's life! Just as unexpectedly, there are new nations and quasi-nations that arise out of the Imperium that virtually no one -- including the people who are part of these would-be nations -- had known had existed. Well, that's life!

The genius of Nassim Nicholas Taleb -- on masterful display in his new book, The Black Swan: The Impact of the Highly Improbable -- is that he has managed to capture what Kapuscinski calls the "essence of truth," as represented by the aphorism "Well, that's life!", in an even more succinct (but no less scientific) concept/turn-of-phrase: "The Black Swan."

This being (in part) a book review, I feel compelled to offer up some sort of recommendation for the book buying public. So here it is: Buy this book. Read this book. Read it carefully. Read it again.

The Black Swan, the book, is the most important book in social science since Adam Smith's The Wealth of Nations. Nassim Taleb's book also happens to be the most significant contribution to the science and philosophy of uncertainty since Andrey Kolmogorov axiomitized probability theory (which along with Bayes, gave us the solid foundation necessary to think clearly about chance) and made progress (with contributions by Chaitin and Solomonoff) towards a more mathematically precise definition of randomness. In terms of epistemology, reading The Black Swan gave me a sense of intellectual kinship that I have not felt since reading Isaiah Berlin's "The Hedgehog and the Fox."

The rest of this essay will be dedicated to explaining, at least in part, why I am heartily endorsing Nassim Taleb's latest book. As a bonus, I will explain why I started The Econophysics Blog.

"Amen," Platonicity, and 'The Little Prince'

I am slightly embarrassed, but not too embarrassed, to admit that reading The Black Swan was an almost quasi-religious experience, full of sublime epiphanies. There were parts of this book where I found myself muttering "amen" -- in the fashion of many in the plebeian parts of Protestantism -- in delighted agreement with the sentiments of its author. (I don't know whether the Reverend Thomas Bayes ever generated an amen from his congregation, but I'm sure he would have given a hearty amen to Nassim Nicholas Taleb.)

All of this genuine enthusiasm is despite the fact that I was expecting to be slightly disappointed by the latest book. After reading his previous book, Fooled By Randomness, I had the impression that Taleb's next book, which became The Black Swan, would be a book that would be geared toward a more technical audience and would be something akin to an anthology of NNT's more formal writings with a sprinkling of more accessible material. Instead, The Black Swan, the book, that we have before us is targeted toward more-or-less the same audience as Fooled By Randomness had, and follows a similar format and tone. But this superficial similarity is (unintentionally) deceptive.

The Black Swan goes into intellectual territory that Fooled By Randomness almost but did not ultimately tread. The best way to distinguish the two books (and contrary to some book reviews out there, there definitely is a distinction) is via the following: Fooled By Randomness raised important and discomforting (which is precisely why it is important) questions about our understanding of, and decision making under, uncertainty; that book inspired the creation of The Econophysics Blog (more on this in the next section). The Black Swan either answers many of the questions raised by the previous book and/or it provides a solid road map to arriving at whatever solutions (and there may ultimately be no solutions) that may exist to the fundamental problem of living in a world where changes in time and chance profoundly affect us all.

In other words, The Black Swan, the book, is one of the best maps available to help us navigate through a world of uncertainty. The idea of distinguishing between useful versus misleading maps is one of the themes that stood out in my mind as I read the book.

Nassim Taleb mentions the analogy to maps in relation to his disdain for what he calls "Platonicity." Taleb defines Platonicity (named after the philosopher Plato) as "our tendency to mistake the map for the territory, to focus on pure and well-defined 'forms,' whether objects, like triangles, or social notions .... we privilege them over other less elegant objects, those with messier and less tractable structures ..." The cardinal sin of Platonicity is that it "makes us think that we understand more than we actually do."

As he makes clear throughout the book, Taleb is not absolutely against the use of intellectual 'maps' (i.e., idealized forms, concepts, methodologies, etc.); what he is opposed to is the uncritical acceptance and use of such Platonic maps and to the use of wrong or misleading maps for inappropriate situations.

Taleb's idea about the foolishness and dangers of Platonicity reminded me of the observations Kapuscinski made about the map used by Antoine de Saint-Exupery as recounted in Saint-Exupery's book, Terre Des Hommes (the English translation: Wind, Sand and Stars). Saint-Exupery was an aviator, adventurer, and writer, who is best known for writing a book that is considered by some to be a classic in children's literature and by others to be a fascinating work of philosophical fiction, Le Petit Prince (The Little Prince).

In 1926, Saint-Exupery was to make a flight from Toulouse (in France), across Spain, to Dakar (in north Africa). Kapuscinski sums up Saint-Exupery's predicament in the following manner (from Imperium):

Saint-Exupery studies the map of his route, but it tells him nothing; it is abstract, general, "vapid." He decides to consult his older colleague, Henry Guillaumet, who knows this route by heart. "But what a strange lesson in geography I was given!" the author recalled. ". . . Instead of telling me about Guadix [Cadiz], he spoke of three orange-trees on the edge of town. 'Beware of those trees. Better mark them on the map.' " And those three orange-trees seemed to me thenceforth higher than the Sierra Nevada." .... "I also assumed a defensive posture vis-a-vis the thirty sheep scattered as in a loose battle formation on the slope of a hill. . . . 'You think the meadow empty, and suddenly bang! there are thirty sheep in your wheels. . . .'"

When Taleb is warning us against the Platonic confusion between maps and territories, what he is suggesting is that we are all in the same predicament that Saint-Exupery found himself in. Just as Saint-Exupery needed a good map to help him navigate in the highly dangerous and risky world of early aviation, we need good maps to help us navigate through a world full of high impact but difficult to predict risks (i.e., Black Swans, the concept). Yet, like that French aviator/writer, we are given useless and/or misleading maps by the so-called experts.

Platonic 'maps' based on (Gaussian) bell-curve probability/statistical distributions (what Taleb calls the "Great Intellectual Fraud (GIF)") are like Guillaumet's map; they are (as Kapuscinski would have put it) 'map-mementos.' Platonic maps are too devoid of detail, too vapid, to serve as a useful guide when navigating a world shaped by extreme, catastrophic risk; those maps exaggerate non-dangers (like Guillaumet's 'giant' orange trees and the platoon of 'fearsome' sheep) while totally ignoring (or severely discounting) very serious dangers (like the actual mountains and platoons of hostile natives that Saint-Exupery was really worried about).

One of many examples that Taleb dissects of a psuedo-expert promoting Platonic/Guillaumet maps of risk is the book on catastrophic risk written by Judge Richard Posner, a highly controversial U.S. federal appeals court judge, law school lecturer, and public 'intellectual' (I use the term loosely here). I can't think of someone who is less qualified by temperament, education, training, skill set, life experience, etc., to claim to be an expert on catastrophic risk. So what does he do? He writes a book about it! (Presumably, it sold well enough.) At least Henri Guillaumet had the decency to be qualified to make his map.

Posner, along with a rogue's gallery of pseudo-experts (and, to be fair, real experts), advocate the use of Platonic Gaussian models of probability and risk despite the fact that one doesn't need to be Ramanujan or Karl Friedrich Gauss to figure out that events like 9/11 and many financial market crashes are double-digit sigma events, i.e., essentially impossible in the bell-curve, GIF world. Frankly, even from a textbook Gaussian perspective, many of these would-be Platonic 'mapmakers' are creating more confusion than clarity by their attempts to over-simplify the risky world we live in. Platonizers, like Posner, are essentially dismissing the possibilities of Black Swans, the concept; because they have seen thousands of white swans, they severely discount or completely dismiss the possibility that 'all swans aren't white.'

What Nassim Nicholas Taleb does so well in this book is to offer up an intellectual map of our risk-filled world (an a-Platonic map) that is more accurate and realistic than the pedantic view of chance that routinely misses the black swans. In The Black Swan, Taleb embraces the emerging scientific field of complexity theory -- especially the fractal mathematics of Benoit Mandelbrot. Power law-Zipf-Mandelbrot-Pareto-Levy-whatever one wants to call it probability distributions, self-similarity / self-affinity, scale-free structures, undefined (or infinite) statistical moments, and 'wild,' fractal randomness, are what Taleb calls "Grey Swans of Extremistan," and they serve as viable alternatives to the Platonic models when it comes to understanding the high impact, almost unpredictable nature of extreme and catastrophic Black Swan events.

I was GIF'ed (and Why Crowds Can Never Be Wise)

When I took my first class in statistics (this was before Nassim Taleb started writing books), I faced an intellectual crises of confidence. I felt I was reasonably good at mathematics (at least the marks I received in math courses and exams said so), but some of what I was being told in my statistics class sounded daft to me.

My biggest dilemma was over the concept of 'outliers.' In a nutshell, outliers are observations or data points that are considered to be so far outside the range of the expected (or hoped for?) bell-curve Gaussian density distribution that they could be ... ney, they should be! ... dismissed. I had a very serious problem with this cavalier dismissal of outliers. Why? It wasn't because I was too dull (or perhaps I was) to understand what the lecturer was saying or what was written in my introductory statistics textbook. I could deal with dogma as well as anybody. No, the problem went much deeper than that.

I'm from a rough working class background. The 'outliers' -- what NNT calls Black Swans, the concept -- that my statistics class so easily waved away are what shaped my life and what shaped the lives of the people I was familiar with. The outliers ... the Black Swans ... are what we -- for better or worse (usually the latter) -- lived by. Most of the Black Swans people like myself faced were ugly: the spectre of poverty, humiliation at the hands of 'betters,' crappy hand-me-down clothes, illness and injury with no time or money to fix it, abusive families, alcoholism, tyrannical bosses, dead-end jobs, hopeless despair, fear. What kept us going was the possibility of a good outlier for a change: winning the lottery, hearing our favorite song on the radio, dreaming of a better life, and a down-on-his-luck kid somehow getting a fancy education.

So I'm sitting in my statistics class trying to get a fancy education, and I'm in the grips of an intellectual (and, almost, moral) dilemma. On the one hand, every fiber of my blue-collar common sense being wanted to point out that it is ridiculous to dismiss some infrequent or improbable event when it is precisely such events that may have the biggest impact in the real world (keep in mind, this was well before NNT started writing books and I had heard of Sextus Empiricus, et al.). From where I came in life, you'd have to be a dummy to think that some out-of-the-blue thing wouldn't change (usually, mess up ... I'm trying to avoid profanity) your life. On the other hand, I knew I would be considered an idiot or a worm by those 'better' than me if I seriously challenged the pedantic notion of outliers.

So I kept my mouth shut (for once in my life). I was a good boy and accepted the 'wisdom' of the bell-curve, along with the idea of outliers. But this always bothered me.

So a few years ago, I bought and read a book by some guy named Nassim Nicholas Taleb titled, Fooled by Randomness (the second edition). This book was usually shelved in the business section in most bookstores, which automatically made me suspicious and reluctant to buy the book since I find most business books by business 'gurus' to be too vapid to be worth my time (I'd rather read a book by Kafka or a book on neuroscience, particle physics, or poker). I was pleasantly surprised to read Dr. Taleb's book. Here was someone who was my social 'better' giving me permission to think the way I always wanted to think. To me it was a proclamation of intellectual freedom.

That is why I started blogging about a year ago and started The Econophysics Blog, which you are reading if you got this far. My original intent was to promote the spirit of Nassim Taleb's ideas ... basically, because the way he thought is basically the way I thought. On the masthead for this blog I could have put, instead of the nerdy stuff I have up there, the motto "I'm an intellectual explorer searching for truth in a world of uncertainty inspired by Taleb, Popper, et al.," but that sounded a bit too soft-in-the-head.

That is also why I am writing this ringing endorsement of Dr. Taleb's latest book, The Black Swan. As I wrote in the previous section, The Black Swan picks up where Fooled By Randomness left off. Any would-be intellectual explorer searching for truth in a world of uncertainty must buy and read this book.

There is one book out there that I will never give a positive review to. I agree with the idea that a book should not be judged by its cover, but some things on the cover, in this case the title, are so odious to me that I can't possibly like it. There is a book out there called The Wisdom of Crowds; the title is daft. Crowds can't be wise. They can never be wise.

Yes, crowds can often have more information and, even, knowledge, but they may also be more ignorant than even the most marginalized individual. Crowds, or 'swarms,' can be more correct than individual judgments, but they can also be terrifically and terrifyingly wrong. But even if crowds were almost always better informed and almost always right, they can still never be wise.

Wisdom is an outlier; wisdom is a Black Swan. By its very nature, wisdom goes against the grain. Wisdom cannot be manufactured by groupthink, or by a swam of bildungsphilisters, or a bildungsphilister(s) that happens to get a publishing deal.

The Black Swan is full of that extremely rare and improbable quality, wisdom. As the book jacket states, The Black Swan, the book, is itself a Black Swan ... the good kind, the kind that is wisdom itself.

Black Swan Virgins (or Did They Really Get It?)

Needless to say, I have no serious criticism of The Black Swan, the book and the concept, or its author. But, since this is a (sort of) book review, I suppose I am expected to say something critical. In that case, the only criticism I can have is directed toward the potential readership of the book.

Most of the book reviews of The Black Swan (with one unfortunate exception) have been positive. As of the time of writing, the book is number five on the New York Times Bestsellers' List. Someone not having read, or not understanding, the book might conclude that all of this good news is confirmatory evidence that the public gets it ... they really understand the Black Swan, the concept and the main point of the book. Unfortunately, as much as I love the book, I am skeptical about whether the reading public really gets it or will get it.

The problem is not with the book, its author, or its editors. The book is well-written and well-thought out. There aren't any major errors or typos in it ... certainly, nothing that would cloud someone's understanding of the main points of the book. No, the problem lies with the readers themselves.

As I wrote in the last section, reading Dr. Taleb's previous book opened up intellectual vistas for me. But this made me wonder, "How can this guy with a fancy pedigree understand things that cab drivers, auto mechanics, factory workers, janitors, truck drivers, et al., understand but those socially 'better' than them not understand?" I eventually got the answers when I read Malcolm Gladwell's excellent profile of NNT in The New Yorker (you can get a similar biography by reading The Black Swan book). Taleb got it 'because' he had experienced Black Swans -- homeland and culture torn apart due to an out-of-the-blue event, and health problems that the GIF-prone mind couldn't have foreseen.

I want to take a slight digression here. I want to make it clear that I do not want to make the same logical mistake the southern Italian professor makes in chapter six of the book. This mistake is something that the book constantly challenges. The mistake -- which Taleb calls "the round trip fallacy" -- is really the idea of the sufficient condition being confused with the necessary condition in formal logic (e.g., "all poodles are dogs" does not make all dogs poodles). The mistake that the Italian professor makes in chapter six is a variant of this fallacy -- with the twist that the notion of assigning causality is involved along with the problem of sufficient vs. necessary.

(By the way, I strongly object to the Italian professor's characterization of Protestants as being incapable of appreciating Black Swans. As Rev. Thomas Bayes and Sir Dr. Karl Popper could have attested to, being Protestant is no impediment to believing in Black Swans.)

Clearly not all Lebanese Orthodox Christians who experienced the civil war and wound up becoming financial traders are Black Swan believing skeptical empiricists. What I am saying is that -- while it is not sufficient to have experienced (suffered) Black Swans to become a Black Swan believing skeptical empricist -- it is absolutely necessary.

It is interesting to note that the two people that Nassim Nicholas Taleb expresses the highest respect towards -- Benoit Mandelbrot and George Soros -- are men who experienced Black Swans in their lives (escaping the Nazis during World War II). It is also interesting to note that my hero and the father of modern probability theory, the mathematician, Andrey Kolmogorov, experienced Black Swans in his life (lost both of his parents at an early age and was raised by his maternal aunts).

One of my other heroes, Ryszard Kapuscinski, would have loved Nassim Taleb's book. Kapuscinski would have really gotten it. It's not because of any quantitative ability; Kapuscinski wasn't Stanislaw Ulam. I doubt Kapuscinski could have solved a stochastic differential equation to save his life, or had the foggiest notion of what a power law or a fractal was.

But, time and time again, Kapuscinski experienced Black Swans. In fact, he made his career out of Black Swans by telling the stories of Black Swans that took the form of armed revolutions, ethnic conflict, deposed Middle Eastern shahs and African emperors, fearful and fleeing colonists, disintegerating empires, and wars fought over football (soccer).

This leads me to another set of fallacies that are directed toward NNT. Many people claim that Taleb and those who are like minded are advocating taking no risks whatsoever. Nothing could be further from the truth!

Obviously, Nassim Taleb, as a financial trader, has had to take a tremendous amount of risks in his professional life. Ditto for George Soros.

Benoit Mandelbrot has taken on a tremendous amount of risk intellectually. Instead of taking the safe and intellectually deadening route of most academics, he has worked at the margins to make the idea of fractals a viable academic discipline. A similar sort of thing could be said about Andrey Kolmogorov.

As for Ryszard Kapuscinski? He once asked the rhetorical question of why he did what he did, "Why do I risk my life time and time again?" Why did he risk his life time and time again when faced with murderous rebels, soldiers, and policemen? The answer: He was on a "mission" ... the mission was to get the story behind the story ... to get to the "essence of the truth."

So those who believe in the Black Swan often take incredible risks ... they've stared the Black Swan in its face and they often want to do it again and again. As Nassim Taleb has so eloquently answered his critics, it's not that he wants people to take no risks, it's that he doesn't want us to take risks in ignorance or blind to the reality of 'wild,' discontinuous randomness.

Other criticisms directed towards NNT -- that he is denying all casuality (no, he is not; he believes that assigning causal links should be based on skeptical empiricism -- which can include applying Einsteinian 'thought experiments'), or that he is opposed to all reductionism (i.e., Platonicity) in science (again, no; he -- as Einstein would have put it -- wants 'science' to be as simple as possible but no simpler) -- can be addressed in a similar fashion. But I must end this essay.

In closing, why am I so skeptical that potential readers (recognizing the fact that buying a book is not the same thing as reading it) won't really get it? Because many readers of this book -- especially the MBA totting types (or want-to-be's), and, I suspect, even people with solid scientific backgrounds -- are Black Swan virgins. They've won't really get it 'because' they have never really experienced Black Swans. I'm not saying these people have never experienced problems or challenges, it's just that the problems they have faced belong in Mediocristan while Black Swans are creatures of Extremistan (read the book and you will know what I mean).

I think Nassim Taleb makes the point about the importance of distinguishing between those who are experienced with Black Swans versus the Black Swan virgins eloquently in the Prologue of The Black Swan (p. xxiv):

I don't particularly care about the usual. If you want to get an idea of a friend's temperament, ethics, and personal elegance, you need to look at him under the tests of severe circumstances, not under the regular rosy glow of daily life. ... the normal is often irrelevant.

There used to be a time when -- even in the swankiest professions and socio-intellectual circles -- there were some old-hands and young 'Horatio Algers' that had experienced Black Swans ... i.e., those who had been tested under severe circumstances. It might be a financial trader who had been affected by the Great Depression or had to flee their homeland with only a suitcase or two. It might be a scientist (natural or social) who survived a war, revolution, genocide, or a famine. It might be a student whose parents didn't know the lingua franca (usually English) and really knew what hardscrabble meant without ever having heard that word because he or she lived it.

But those times have passed. It is ironic that -- as I wrote in my previous blog post, Tyranny of the Power Law -- that the very thing that brought the 'elite' success in life, the power law -- a symptom of the Black Swan, makes people blind to Black Swans by allowing the Black Swan blind to 'protect' themselves by entrenching their privilege.

Anyone who reads and understands The Black Swan, the book, will realize, however, that this can't last. Black Swan virgins -- especially those who are responsible for billions of dollars (or pounds, or Euros, etc.), or those responsible for the lives of millions (or even billions) of innocent people -- will eventually experience the Black Swan. Sadly, for innocent pension holders or even more innocent peace-loving, law-abiding citizens the world over, these Black Swan virgins won't know what to do. They'll fumble at the moment of destiny because they were blind to the fact that life is punctuated by extreme risks and they were blinded to that reality by the Platonized idea that risk can be 'managed' or controlled ... "risk leaps not glides."

Even a book of rare genius like Nassim Nicholas Taleb's book -- unless read carefully and with humility -- can do much to prepare these Black Swan virgins. When they face their Black Swan -- what the truly great historians and thinkers used to call 'destiny' -- it will be too late. Well, that's life!

Makings of a Chinese Stockmarket Bubble?

2007-04-29T20:52:00.000+01:00

China is in the midst of a stockmarket frenzy. According to an article in The Economist magazine (April 26, 2007), new accounts at stock brokers are being opened at a rate of more than 200,000 a day (e.g., more than 310,000 on April 24th of this year). Many of these punters are relatively new to the market and are often either unsophisticated or relatively low-income (including, students and old-age pensioners).

What is fueling this madness for stocks? Despite a couple of scares earlier this year (February 27, and April 19), phenomenal returns (for now). E.g., the Shanghai Stock Exchange's composite index rose by about 130% in 2006 (and is still rising). (See the chart below.)

Having seen some newspieces from China Central Television's channel 4 news on the latest stockmarket craze, I can see how much the stockmarket has permeated daily life in China.

It's worth noting that another factor, besides hyperbolic returns, is driving this 'investing' frenzy -- consumer technology. By "consumer technology" I don't mean China's equivalent of tech stocks (although I'm sure they are enjoying a boom). Instead, it is the growing availability of communcation devices like cell phones, instant messaging, and broadband Internet connections that have reinforced and further enabled this stockmarket 'madness of crowds.'

So is this a bubble? It certainly has all of the earmarks of a stockmarket bubble that will eventually burst. The recent past has demonstrated that Chinese stockmarkets (in Shanghai and Shenzhen) are vulnerable to market volatility as well as to macroeconomic shocks and policy changes by the Chinese Communist Party.

One of those Chinese would-be investors, when describing China's stockmarkets, quoted by The Economist summed it up best: "It's like a casino set up by the Communist Party." If the CCP isn't careful, they will find themselves in quandry (which they may already be in). A rising stockmarket keeps the public (especially the growing middle class) mollified and gives the CCP more credibility. On the other hand, a bubble that burst could cause widespread anger toward the CCP. As Western capitalists can attest to, it is rather difficult (if not impossible) to reconcile those two agendas.

The Economist on Credit Derivatives and Market Liquidity

2007-04-27T02:08:00.000+01:00

The Economist magazine has a couple of interesting (and related articles) on finance and investing.

In its special report, Credit derivatives: At the risky end of finance (April 19, 2007) , The Economist closely examines both the benefits and potential risks of credit derivatives. The pros of credit derivatives include the possibility that they make investing and trading in the bond markets more palatible. The cons are that they might be a ticking financial time bomb -- a "financial weapon of mass destruction" in Warren Buffett's phraseology -- that are vulnerable to shifting market conditions (e.g., a major increase in interest rates).

In this week's issue, Liquidity: Deal or no deal -- A new measure of market health (April 26, 2007), The Economist highlights how the Bank of England is trying to clear up the muddle about how to measure market liquidity. The Bank of England's measures (they have three) of liquidity is based on the "ease of buying and selling financial assets." According to its measures, the markets are flush with liquidity. Why? The article offers many explanations (hedge funds, financial innovations -- like credit derivatives, etc.), but it also points out that this surge of liquidity is a fickle thing. I.e., there will be more liquidity so long as investors are confident; when confidence wanes, liquidity probably will drop as well.

Psychology of Evil (and Love)

2007-04-22T08:01:00.000+01:00

Reflecting upon the tragic events of last week, I thought it would be helpful to offer up some material that might help put the most recent man-made tragedy (and, sadly, tragedies to come) into perspective using the tools of science.

Renowned social psychologist Philip Zimbardo has recently written a book about his unique take on the (in)famous Stanford Prison Experment -- where ordinary college students were put into a psychology experiment that gave some of them extraordinary power over the lives of other subjects -- titled The Lucifer Effect: Understanding How Good People Turn Evil. The New York Times recently interviewed Prof. Zimbardo about his views on the social (and personal) psychology of evil, Finding Hope in Knowing the Universal Capacity for Evil (April 3, 2007). (A video of the interview can be seen at this link.)

Philip Zimbardo's social psychology experiment was very similar in spirit to another (in)famous experiment carried out by fellow social psychologist (and childhood friend from the Bronx), Stanley Milgram. The Milgram Experiment involved testing how far subjects were willing to follow orders -- no matter how cruel or evil -- by putting them at the control of a seemingly authentic electroshock device hooked up to another human being. The late Prof. Milgram wrote up his findings for a popular audience in his book, Obedience to Authority, which remains a classic in popular science literature.

A more hopeful finding worth noting here came from the research of another noted experimental psychologist, Harry Harlow. Harlow (as well as others, including John Bowlby) managed to establish the concept of the supreme importance of love on a scientific basis. Science writer, Deborah Blum, has written a masterful book describing the science of love in her book, Love at Goon Park: Harry Harlow and the Science of Affection.

Profs. Zimbardo, Milgram, and Harlow, can be loosely grouped into the 'situationalist' school of psychology. The experimental legacies of all three of these giants in social science provide a solid basis for the idea that circumstances and situations play larger roles in human tragedies than we may feel comfortable with.

I would like to end this particular posting with a personal sentiment. I sincerely believe that evil cannot be overcome with more evil ... to do that only perpetuates more evil. I also believe that hate cannot be defeated with more hatred, nor can inflicted hurts be healed by inflicting hurt on others. Evil can only be overcome with good; hatred can only be vanquished with love.

It may sound slightly 'hippy-ish' to advocate for more love in the world, but -- as Harry Harlow, et al., demonstrated empirically -- the need for more love in our flawed and hurting world is, from a hard-headed (but not hard-hearted) scientific point of view, absolutely correct.

Mimicking Soros, Dangers of Low Volatility, & Collusion in the Music Industry

2007-04-18T16:14:00.000+01:00

I've noticed several interesting articles in The Economist magazine recently that are worth noting.

In his/her column, Soros on the cheap (April 4, 2007), Buttonwood makes the case for currency trading as a valuable addition to an investment portfolio. In particular, currency trading based on exchange rate models that take into account the 'carry trade' (an arbitrage technique which is similar to short selling), momentum, and purchasing power parity, have shown themselves to be profitable.

In last week's column, Sting in the tail: Is low volatility making the world too complacent about risk? (April 12, 2007), Buttonwood makes an even more convincing argument that instruments, practices, and institutions in the financial markets that leads to a relatively low volatility environment most of the time may wind up increasing 'tail risk' (i.e., extreme risk). Low volatility may be a 'false dawn' -- or perhaps even a cruel joke being played by the forces of market randomness -- that lull investors and traders into a false sense of security ... suckering people along into making bad financial decisions until catastrophe strikes.

Finally, in the March 29, 2007, 'Economics Focus' column, Silent orchestration: Can record companies act in concert, even without agreeing to do so?, The Economist examines the possibility that there is tacit collusion in the music industry by applying the logic of game theory. This type of analysis is very important to monopolies, antitrust, and competition laws & regulations. As the column points out, it is difficult to hold a cartel together (tacit or explicit), but, using game theoretic methods, it isn't impossible.

Tax Time in the US

2007-04-17T16:25:00.000+01:00

Federal (and most state) income taxes are due today in the U.S. A New York Times article by David Cay Johnston reveals that the middle-class are more likely to be audited this tax season by the I.R.S. than those wealthier them. Much of this seems to stem from the increased complexity of the tax code under Republican rule for most of the decade to date. This is ironic since many Republicans have traditionally advocated for simpler tax laws.

Intellectual Property Law vs. Open Source Economics

2007-04-05T20:30:00.000+01:00

Today's New York Times (April 5, 2007) had an 'Economic Scene' article by economist and technology expert Hal R. Varian: Why That Hoodie Your Son Wears Isn’t Trademarked. In his article, Prof. Varian makes a persuasive case for the idea that "not every industry necessarily benefits from strong intellectual property protection. In some cases, it appears that lack of protection can lead to a more vibrant and dynamic industry."

The example that Varian highlights in his article is a think-piece written by two law school professors published on-line at Public Knowledge. According to both of the law school profs as well as economist Hal Varian, what is normally deemed "piracy" of intellectual property (i.e., some sort of alleged infringment of copyright, trademark, patent, and/or other variants of intellectual property law) actually spurs innovation and makes both good economic and business sense. As Prof. Varian puts it:

Mr. Raustiala and Mr. Sprigman argue that the lack of intellectual property protection actually promotes the functioning of the industry. If the extension of copyright to fashion prevented clothes manufacturers from copying each other, the industry would be ceding a major role to the lawyers and become much less creative. We’d see the same thing year after year. In other words, women’s fashion would look much more like men’s fashions — boring, boring, boring.

This line of reasoning is very similar to the rationale for the open source movement in the computer software community. A thorough analysis of the legal, economic, and technological impacts of the open source idea is provided in Open Source Software Licensing, a research paper by Harvard Law School graduate, Steve Lee. A nice summary of the open source philosophy is provided by Andrew Leonard's Salon.com article, License to Be Good.

The cliff-notes version of the economics involved in analyzing whether or not there should be stronger intellectual property protection or not boils down to the issue of fixed costs versus marginal costs. In economics, marginal cost is the rate of change of costs (in calculus terms, the first derivative of the cost function). Many technology-centric and other types of industries that are heavily tilted toward intellectual property (e.g., music downloads) have marginal costs that are extremely low and even approach zero -- especially in light of the internet's ability to distribute and reproduce materials at low costs.

On the other hand, these industries often do have substantial fixed costs (in economics, these are costs that must be incurred in order to produce the goods or services in question; these costs aren't usually adequately reflected in marginal costs). So an economist's take on a lawyer's question regarding intellectual property boils down to this: How do we balance the need to recoup fixed costs versus the benefits of having more relaxed intellectual property laws, in the context of the fact that the marginal costs of copying and redistributing material often approaches zero, in the internet age?

Hal Varian's opinions, as well as that of most of the others cited here, on this matter is, not that there is no need for intellectual property law, but that there is another side to the argument (the benefits with low costs of a more relaxed intellectual property regime). This is a debate that is central to the information age we live in and I'm glad that Varian, et al., have shown us that there truly is a debate.

Book Review: The Mathematics of Poker

2007-04-01T08:01:00.000+01:00

The game of poker is a fascinating mix of mathematics and psychology. The combinatorial and probabilistic nature of the shuffling and dealing of cards -- as well as the uncertainty associated with competing against people with differing personalities and backgrounds -- suggests that a good poker players should be, at least on an intuitive level, good mathematicians. The need to make major decisions under pressure also suggests that poker is a case study in applied psychology.

As someone fascinated by both econophysics and poker, I drew the conclusion that mathematics could be fruitfully applied to both the more obviously 'mathematical' aspects of poker as well as the psychological/decision-making aspects of poker (via game theory). With the ongoing popularity of poker on television, on the internet, and in card rooms, as well as a growing body of poker 'literature,' I naturally expected there would be at least a few books available that took on poker mathematics. Sadly, the vast majority of poker books only deal with 'math' on a purely computational or numerical basis -- i.e., they explain or offer up various types of odds associated with poker and not much beyond that -- rather than applying the analytical tools provided by mathematics in its more purer sense.

The Mathematics of Poker by Bill Chen -- a mathematician, part time pro poker player, and full time financial quant at Susquehanna International Group -- and poker pro, Jerrod Ankenman, finally addressed many of my musings on the intricate relationship between poker and mathematics. Although this book is not for everyone, especially those who are faint of heart when it comes to equations and formulae, it should be highly useful to quantitatively minded poker players and fans as well as to finance types that may (or may not) be surprised to find so many commonalities between poker and quantitative finance.

One of the interesting attributes of this book is that, despite a plethora of equations and semi-formal mathematical expressions that very few poker players will actually work through at the table, the authors take the position that the mathematical analysis and reasoning they use in this book is designed to make the reader more profitable poker players. This practical stance actually enhances the intellectual credibility of this book: While the more self-consciously 'intellectual' works that tackle 'poker' deal merely in abstract scenarios that differ dramatically from real-world poker, Chen & Ankenman's book offers up analysis (even when using 'toy games') that is tied to what poker actually looks like.

Some of the high points of this book are: the book's explanation of how mathematical statistics and probability -- especially Bayesian approaches -- might apply to poker decisionmaking (Parts I & IV), the application of mathematical game theory to the game of poker (Parts II, III, V), the concept of "effective tournament size" (where tournament payout structure alters the number of 'double ups' needed to make money in a poker tournament) (Part V), a quantitative approach to poker backing agreements (Part IV), the important role that exponentials and logarithms play in the mathematical analysis of poker (Parts III and IV), risk management for poker players (Part IV), and the scientific approach to the 'art' of hand reading (i.e., making an educated guess of the distribution of cards your opponent may have) (Part II).

An especially fascinating aspect of this book is how the authors make some interesting analogies that connect poker to quantitative finance. The idea of maximizing logarithmic utility, which is at the heart of a lot of quantitative finance, is discussed in detail in connection with profitability in poker play (I should note that the authors call this concept the 'Kelly Criterion' or 'Kelly betting,' but for reasons beyond the scope of this blog post, I don't quite agree with this characterization because the Kelly Criterion is a much deeper concept, IMHO, than maximizing log utility). The book also bring in other concepts from quantitative finance and financial economics into poker analysis, including the Sharpe ratio, financial options (real options), and modern portfolio theory.
The best part of this book was its explanation of the 'risk of ruin' and how it relates to poker play over time. I have read many books on probability, statistics, general mathematics, and gambling over the years and I have always felt frustrated by the lack of a clear explanation of the rather useful but basic concept of the risk of ruin. The Mathematics of Poker gives, by far, the best explanation of the risk of ruin I have ever read.

Although this book makes many very excellent points and should be a valuable addition to anyone intersted in the subject matter, this book does have some flaws. One of the most obvious flaws is that it has a number of typos and errors. I wished the authors or the publishers had invested in LaTEX typsetting (it doesn't appear that way to me). Having pointed this out, however, I should, in the book's defense, also note that: (a) most of the errors are minor and of a typographical nature rather than a substantive nature, and (b) the authors and publishers are putting out an errata and have been making corrections to new printings of the book (details on this can be found on the book's website) -- which are the responsible things to do (that many others neglect to do in the technical publishing world). Another criticism along the same lines is that some of the notation is confusing (e.g., the Greek symbol for 'alpha' means radically different things in different parts of the book) and should have been better thought out.

The only other major criticism I have the book is 'Part III: Optimal Play.' Although game theory is utilized throughout the book, Part III is where the bulk of the application of game theory to poker takes place. So it frustrated me to find this part to be tedious even to someone who is an avid reader of highly mathematical and technical material. Having said that, however, I should note that there are definitely interesting and worthwhile points of wisdom made in Part III. Furthermore, the other parts of the book are so interesting in and of themselves that Part III can be safely skimmed in order to 'enjoy' (to the extent one can 'enjoy' a mathematics book) the book as a whole.

The final point that needs to be made about this book are the mathematical prerequisites needed to read this book. The authors state that they have kept the prerequisites to a minimum and that someone with a very solid high school college prep mathematics knowledge base can understand this book. Although I think the authors are sincere in their claims, I think this book would be a challenging read for those who are limited to that criteria. I think a more realistic mathematical prerequisite for reading this book is either someone who has had at least some education in calculus (which the authors occassionally throw in) or someone who regularly reads math books -- they could be 'pop' math books -- that have equations and algebraic manipulations in them. If you have that level of mathematical sophistication -- which is still a fairly low standard -- you should do alright with going through the type of reasoning used in this book.

In summary, I believe that this book does an excellent job of finally addressing what had been a glaring omission in the poker literature: the application of mathematics (as opposed to just numbers and computations) to poker. As Chris Ferguson, a World Series of Poker main event champion and a holder of a PhD in computer science from UCLA, said in his endorsement of the book, "If I ever find myself teaching a poker class for the mathematics department at UCLA, this will be the only book on the syllabus."

Bill Chen & Jerrod Ankenman's book may do more than offer up a route to intellectual exploration, however. As Jeffrey Yass, Bill Chen's boss at Susquehanna, states "In the same way that quants and mathematicians took over Wall Street in the late 80's, mathematical methods will dominate poker in years to come."

Air Out of the Real Estate Bubble?

2007-03-28T20:30:00.000+01:00

With each passing day, there seem to be more and more signs that the air is coming out of the real estate bubble in the U.S. News of layoffs at mortgage lenders and investigations of some mortgage lenders seem to be consistent with the popping of a bubble. Most of the economic data and trends related to real estate are also consistent with a downturn in real estate. The Economist magazine has an article (March 22, 2007) analyzing the rise in foreclosures and the downward direction of the real esate market.

Mad Money Gone Mad?

2007-03-20T21:11:00.000Z

I have already put in my two cents about Jim Cramer (the host of CNBC's 'Mad Money') in a previous blog post: "Mad Money" Should Make Average Investors Mad (March 26, 2006). It seems that Jim Cramer has gone to new levels of madness by revealing how he and other hedge fund managers (Jim Cramer used to be in the hedge fund game) manipulated (either supposedly 'legally' or illegally) market information in order to boost their short-sell positions. One place you can read about this is in the New York Times DealBook blog (March 20, 2007). You can also see the video of the interview at YouTube.

If what Jim Cramer is saying is true, then the Securities & Exchange Commission (SEC) should take a serious look into these practices. One of the tactics, which Cramer calls "formenting," involved feeding deliberately false information into the markets. I'm not sure if this type of activity would fit into the 'fraud on the market' theory of securities law and regulation, but it's worth investigating.

As for Jim Cramer's other comments -- about how he thinks it's a swell idea to basically lie and defraud people as a hedge fund trader -- is so digusting to me that I can't seem to find the words to condemn him. I will say one thing though ... if you notice that my previous blog post warning people about the empirically demonstrated negative impact on the investment returns of those who follow Jim Cramer's Mad Money advice was written about a year ago ... at least my conscience is clear. The Econophysics Blog did a public service in putting up that post. This latest shenanigans by Jim Cramer proves up the wisdom of that year-old warning.

China & Grey Tuesday

2007-03-09T08:29:00.000Z

As I've stated in the past, I try to avoid making this blog too event-driven. I'd rather let things happen in the markets, see if they are worth commenting on, and, if it is worth commenting on, try to analyze events after the dust has settled and clearer heads prevail.

Having said that, I think it is worth pointing out one aspect of last week's sharp and sudden drop in the financial markets. Dubbed 'Grey Tuesday' by some, the events of February 27, 2007 -- where the Dow Jones dropped by more than 400 points in a matter of minutes (a rate of decline that had been hitherto unprecedented) -- garnered a lot of attention.

A lot of the 'analysis' that was given on television seemed to focus on a lot of things (the terrorist attack in Afghanistan while Dick Cheney was visiting, etc.) that seem to me to be largely irrelevant. The one bit of news that probably did have a significant impact was the sharp drop in Chinese share prices that immediately preceded the drops in Western stock markets.

China had been experiencing eye-popping rise in stock market valuations. This brought the Chinese markets (in Shanghai and Shenzhen) to the attention of wary Chinese policymakers who were concerned about over-heating markets and rampant irrational speculation. These concerns moved Chinese regulators to talk down their stockmarkets as early as January of this year. Apparently all of these attempts to cool Chinese markets came to a head at the end of February ... much to the chagrin of traders and investors around the world.

'Grey Tuesday' -- or whatever one wants to call it -- should serve as a wake-up call to the investing community. This is yet another example of how much global markets are inter-connected to one another. Claims of adequate diversification via a simplistic approach to 'global' investing is -- as the most recent Buttonwood column (in The Economist) points out -- should be met with skepticism. Correlations and covariance between financial markets in different geographic regions are not static ... they are dynamic and market values tend to move together in the most inopportune ways (in downward directions almost simultaneously).

The rapid drop in market prices is also another example of the often 'wild' nature of randomness. Events in financial markets is a lot more jumpy than what most finance textbooks would suggest.

What do the Oscars have in common with hedge funds?

2007-02-25T09:39:00.000Z

Answer: Film financing.

I just noticed the New York Times Dealbook's posting about how hedge funds have gotten involved in film financing. Although a nod from the Academy of Motion Picture Arts and Sciences will be a boost to the egos of these would be movie moguls, I suspect that they are much more interested in profits. It is from this perspective (the monetary one rather than the artistic one) that we see how financial and commercial randomness can prove more fickle than the whims of the Academy's voters.

According to empirical research done by economist Arthur De Vany, financial returns from investing in movies seems to be more uncertain than the prospects of winning an Oscar. This situation is caused by the fact that movie success (and, more often, failure) tends to be consistent with the power law -- specifically, a few movies account for most of the profits of the film industry during any given period. The power law is often associated with 'wild randomness' (a favorite topic of this blog) -- i.e, where the ability to pick winners & losers is hampered by bewildering layers of complex interactions and 'jumpiness' that occur when films are released in the marketplace.

Even if hedge fund managers and traders are disappointed by the results of the 79th Academy Awards or by the byzantine nature of Hollywood financial practices, they can take heart in the Bush administration's recent decision to not regulate the hedge fund industry. If there was an Academy award for acting surprised by this decision, then it would surely go to some lobbyist acting on behalf of the hedge fund industry.

Profile of David Swensen, Yale's legendary investor

2007-02-22T20:46:00.000Z

This Sunday's New York Times had a fascinating profile of David Swensen, Yale's legendary chief investment officer and a faculty member of its business school: For Yale’s Money Man, a Higher Calling (Feb. 18,2007). In over two decades, Mr. Swensen "has generated an annual compound growth rate of 16.3 percent" for Yale's endowment "beating the performance of Harvard’s endowment and that of every other major school in the country over the same period." This amazing performance over the years has accounted for over $7.8 billion into Yale's coffers ... making him the largest financial contributor to the school over the last 20 years.

In the article, David Swensen mentions two contrarian maxims that have guided him both as an investor and as a man over the years. The first of these maxims is that he looks for "people who define success by generating great returns, not by making as much money as they can." This may sound odd coming from one of the greatest investors in recent memories but it makes a lot of sense in both a practical and a philosophical way.

From a practical perspective, it makes sense for an investor to entrust money to someone who is more focused on performance rather than on generating fees. As Mr. Swensen explains it:

“If you make money personally by gathering a huge pile of assets, it is great for the management company because they make bigger fees,” Mr. Swensen says. “But if the fund goes from $2 billion or $3 billion to $20 billion, they are inevitably going to reduce their ability to generate investment returns. Size is the enemy of performance."

From a philosophical perspective, Mr. Swensen's first maxim is consistent with a meritocratic view of life. In other words, it's performance and merit that should matter most rather than just having access to a pile of assets.

Mr. Swensen's second maxim is that the art and science of investing can be applied to things beyond making the wealthy wealthier. Investing can be used to support non-profit causes and other endeavors that can make contributions to sorting out the world's problems. This second maxim has led to Mr. Swensen spurning generous offers to become an investor in the private sector for substantially higher pay.

Besides his contributions to the practice and philosophy of investing, David Swensen is an author of two of the best books on finance ever written: Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment, and Unconventional Success: A Fundamental Approach to Personal Investment. Anyone serious about learning the art and science of investing should read both of Mr. Swensen's books.

Partnoy's Non-Complaint for Hedge Fund Activism

2007-02-18T09:35:00.000Z

This sunday's New York Times had a column by Mark Hulbert that describes research by a group of finance and law professors arguing that hedge fund activist interest is good for share values for up to a year: A Good Word for Hedge Fund Activism (Feb. 18, 2007). This would contradict the negative image held by some people that hedge funds are solely concerned about short-term profit and may not enhance shareholder value for relatively long periods.

The research -- consisting of a working paper, Hedge Fund Activism, Corporate Governance, and Firm Performance, by a cadre of finance and law professors -- does bolster some of of Mark Hulbert's points. However, a slightly closer perusal of the original research paper reveals that the Times article is being a bit too optimistic about the benefits of hedge fund activism.

As the paper makes clear, a lot of the abnormal returns from hedge funds taking substantial positions -- by 'substantial,' I mean the 5% or more of company's outstanding shares that need to be acquired to trigger securities law requirements to file with the the Securities and Exchange Commission (SEC) -- in targeted companies come from the actual or implied hostility of the acquisition (e.g., disagreement with management about business strategy or sale of the company). Hedge fund activities that targeted more mundane corporate governance issues did not generate much in the way of abnormal returns.

Furthermore, the data set that the researchers looked at seem to me to be somewhat limited. This limitation is due to the fact that hedge funds have limited reporting requirements with the SEC and other financial regulatory authorities (hence their appeal to some investors). The data that the research looks at is limited to acquisitions of publicly traded shares that are substantial enough to trigger reporting requirements. By no means does this data set represent the bulk of hedge fund activities.

One final bit of info worth noting is that one of the authors of the working paper is Frank Partnoy, a law professor in San Diego. What he is best known for, however, was his stint as a derivatives salesman/trader at Morgan Stanley. He wrote up his experiences at Morgan Stanley in the highly informative and entertaining (but not particularly flattering for Morgan Stanley or his previous employer, CS First Boston) book, FIASCO: The Inside Story of a Wall Street Trader ... a book that has been favorably compared to the Michael Lewis classic, Liar's Poker. While Frank Partnoy is no Philip Roth, Prof. Partnoy is an excellent writer/story-teller by the standards of financial traders or lawyers.

The Shock of Uncertainty

2007-02-14T22:37:00.000Z

Nick Bloom, an economist at the London School of Economics and Stanford, has done some fascinating research modelling the effects of uncertainty shocks on the investment decisions of firms and other macroeconomic actors. The gist of his research is that -- rather than focusing on the effects of macroeconomic shocks on the expected value (i.e., the first statistical moment of a probability distribution) of macroeconomic variables -- Prof. Bloom focuses on estimating the effects that volatility (i.e., the second moment of a probability distribution) shocks may have on firm level decisions in the macroeconomy.

Using numerical simulations with MATLAB (a computational mathematics software package), Dr. Bloom makes some interesting conclusions regarding what uncertainty shocks (i.e., second moment shocks) can do to economic decisionmaking. One of the many conclusions of the research is to confirm Ben Bernake's (formerly, a Princeton economist, but now the head of the Federal Reserve) previous research concluding that there is a 'real option' for firms to wait-and-see before making major decisions (such as making capital or labor investments). Another interesting conclusion is that second moment shocks tend (with the exception of the Great Depression period) to be transitory -- spikes in volatility lasts for a few months before settling back down.

Perhaps the most interesting finding by Prof. Bloom is that his model seems to fit well with what happened during the period on and following the 9-11 terrorist attack: a sharp spike in stock market volatility, many businesses taking a holding pattern before making major investment decisions, and, eventually, a return to relative normalcy (although it should be noted that the scandals involving Enron and Worldcom added further spikes in volatility that had a sort of knock-on effect that made the transition back to a lower volatility environment more uncomfortable than it otherwise could have been).

There are other findings that should be of interest to readers of this blog. You can download Nick Bloom's paper, The Impact of Uncertainty Shocks: Firm Level Estimation and a 9/11 Simulation, by clicking the link. A layman's overview of the research can be found in the Economics Focus section (Feb. 1, 2007) of The Economist: Momentous modelling: When terrorists strike, what happens to investment and jobs?

Uncertainty About Financial Risk

2007-02-05T20:19:00.000Z

The Economist has an interesting article (Feb 1, 2007) on uncertainty regarding financial risk. The article briefly explores whether financial risk is being properly mitigated or whether people are simply paying lip service to risk management and that, in reality, hidden risks are poised to send shock waves throughout the markets.

As The Economist points out the 'great-and-good' at Davos and elsewhere seem to be mindful of risk, yet:

[A]s the Bible says, “by their fruits ye shall know them”. Banks are still financing leveraged buy-outs, junk bonds are offering their lowest spreads since March 2005, and the cost of insuring against a share-price fall, as measured by the Chicago Board Options Exchange Volatility Index (Vix), is low (see chart below). Financiers may be worrying about risk, but they do not seem to be doing much about it.

Perhaps the most succinctly wise way of thinking about financial risk is what Warren Buffet had to say about it: “It's only when the tide goes out that you learn who's been swimming naked.” In other words, we won't know whether the optimists or the pessimists are right about risk until the proverbial "tide goes out."

Even more tyranny of the power law -- An audit of affluence (Financial Times)

2007-01-28T08:57:00.000Z

The following is an article from the Weekend section of the Financial Times (Jan. 26, 2007). You can consider this to be more evidence to support my fears over what I have termed the 'Tyranny of the Power Law'. One of the research articles that the FT piece cites as evidence for decrease in meritocracy in the U.S.A. (as measured by decrease in intergenerational income mobility) is found at the Social Science Research Network. This study is in line with other econometric and/or economic studies showing similarly disturbing trends toward an American plutocracy (as opposed to meritocracy).

I find all of this to be disturbing enough to post the article in full on this blog. I strongly believe in meritocracy. We desperately need more of it not less. I hope you will agree.

----

An audit of affluence
By Chrystia Freeland
Financial Times, FT.com
Published: January 26 2007 15:25 | Last updated: January 26 2007 15:25

When I was reporting on Russia in the 1990s, one of my friends’ favourite observations was that “everything Marx taught us about communism was false but everything he taught us about capitalism was true”. As the nation’s vast natural resources were parcelled out among a handful of oligarchs, it was hard to disagree. But the Kremlin’s crony capitalism was so openly rigged that it was also easy to point out that the western version of a market economy was a different beast altogether.

The contrast seemed sharpest with the US. The great thing about this country, a European-born financier pointed out to me when I arrived last year, is that everyone believes he can succeed. For the billionaire, that made America the best place in the world to be a plutocrat. In Europe, he felt, when people saw a rich man they wondered how, as Proudhon famously observed, he had stolen his way to wealth: “But in America, when people see you are rich they ask themselves how they can become rich, too.”

This perceived equality of opportunity, and its impact on class relations, has long been a fond theme for America’s boosters. Alexis de Tocqueville was struck by how American servants weren’t very servile because “at any moment a servant may become a master and he aspires to rise to that condition”.

Nowadays that aspiration has looked harder to achieve. Two recent academic studies have found that some parts of Europe have become more meritocratic than the US: poor children in the Nordic countries stand a better chance of rising through society than their US counterparts. As for inequality of outcome, it has become so pronounced that it is being recommended as an investment strategy.

Citigroup analysts Ajay Kapur, Niall Macleod and Narendra Singh are leading advocates of this approach. They have coined the word “Plutonomy” to define countries – chiefly the US, Canada and the UK – where “economic growth is powered by and largely consumed by the wealthy few”. In a twist my Marx-schooled Russian friends would surely appreciate, they point out that savvy investors can take advantage of this trend by buying Plutonomy stocks, chiefly companies such as Bulgari and Richemont that produce “toys for the wealthy”.

The analysts offer a warning. In the Plutonomies, they point out, “political enfranchisement remains as was – one person, one vote”. This tricky fact “will probably, at some point, lead to a political backlash”. Indeed, as the 2008 race for the White House heats up, some politicians, notably former senator John Edwards, are picking up on the gap between rich and poor.

That could be dangerous for the plutocrats and a few seem to have realised that. You could call them the Buffett billionaires – those self-disciplined super-rich who have decided that frugality is wiser than flaunting it. A co-founder of a private equity group recently bragged to me that his Christmas present to his legendarily parsimonious wife was a “re-gift” – he got it in exchange for a fancy tie he had been given, which he took back to its Fifth Avenue vendor for store credit. A technology company boss told me this month he “doesn’t really like to consume” and that he tries to keep his business expenses to about $1,500 a week – a lot of money for ordinary North Americans but positively stingy for the CEO set.

In some New York circles, certain types of luxury consumption might even be becoming gauche. If, for example, you belong to Nora Ephron’s literary coterie I suspect you won’t be showing off one of the $2,600 handbags she gently mocks in her bestselling new collection of essays. A few executives who are still of the Bonfire of the Vanities school have found their habits to be worse than a faux pas – they turn out to be a sacking offence. This week’s scalp was Citigroup’s Todd Thomson, whose lavish office was nicknamed the “Todd Mahal” and included a wood-burning fireplace. Earlier this month it was Bob Nardelli, whose truculent defence of his compensation of more than $120m since joining Home Depot in 2000 helped provoke his ouster.

Conspicuous frugality is exactly the sort of self-preserving capitalist trick that ultimately defeated my Russian friends’ Soviet forebears. It is definitely an approach my own family’s most fervent capitalist – my penny-pinching, Glaswegian grandmother – would endorse. But I hesitate to predict that all of Manhattan will embrace her Scottish parsimony. One of my grandma’s signature habits is an absolute refusal to spend a quarter in our town’s parking meters, a philosophy particularly memorable if you have ever chauffeured her around, and around, and around Main Street in search of a free spot.

I thought of her when a very different sort of driver made headlines in The New York Times this week. The 92nd street Y – the exclusive Upper East Side pre-school which figured in Wall Street analyst Jack Grubman’s downfall – has warned parents their tots’ all-important letters of recommendation to kindergarten will be in jeopardy if their chauffeur-driven SUVs do not stop blocking the entrance to the school. Instead, their hired drivers have been instructed to find a legal parking spot or circle the block a few times while the parent or babysitter takes her toddler inside. That is good news for Plutonomy investors, but, at least when reporters are around, the smartest plutocrats might want to try taking the train.

chrystia.freeland@ft.com

More columns at www.ft.com/freeland

* Ajay Kapur, Niall Macleod, Narendra Singh, “Plutonomy: Buying Luxury, Explaining Global Imbalances,” Citigroup Research, October 16, 2005 and “Revisiting Plutonomy: The Rich Getting Richer,” March 5, 2006.

Copyright The Financial Times Limited 2007

Contango Fango: The languid state of oil & commodity prices

2007-01-23T20:34:00.000Z

This post is a follow up to a previous blog post Glenn Gould and Commodity Prices (Nov. 9, 2006). The Economist magazine's Buttonwood column had an article on the ongoing languid state of oil and copper prices: Oil's not well: A fall in commodity prices raises concerns about the appetite for risky assets (Jan. 11, 2007). According to the article, January 9th of this year saw crude prices at an 18-month low. Copper prices, which had risen to lofty levels, aren't doing much better. All of this is despite rather compelling stories of increased geopolitical risk which should increase commodity prices and decrease emerging market asset values (it might have the latter effect, but it is not currently having the former effect).

The Buttonwood piece cites several reasons for why commodity prices are in a slump and also debunks some reasons that have been offered up for the current languidness of oil and copper prices. As I had suggested in the 'Glenn Gould ...' blog post, the slump probably has more to do with the fickleness of speculative capital than any of the rationales that have been offered up. Buttonwood concurs. As the article points out, speculation in commodities futures created a phenomena known as 'contango' -- where roll yields are negative (i.e., futures prices are higher than spot prices) and futures investors had a harder time making a profit (since they can't count on futures prices to rise to future spot prices). Factoring this in means that commodities speculators lost money even if the spot prices of commodities had remained high (and even that might no longer be true).

Neuroeconomics of Spendthrifts vs Tightwads

2007-01-21T02:19:00.000Z

John Tierney's column in the New York Times (January 16, 2007) discusses neuroscience / neuroeconomic research into the difference between the minds of spendthrifts versus the minds of tightwads. According to research done at Carnegie Mellon, the difference can be explained by the relative differences of how different people experience the pain of spending (or not spending): More pain from spending, more likely you are to be a tightwad; less pain, more likely you are to be a spendthrift. A lot of this type of research is carried out by using functional M.R.I. machines scanning subjects' brains as they make economic decisions in a laboratory setting.

Experimental Economics Article on the FT

2007-01-07T08:01:00.000Z

Tim Hartford's Undercover Economist column on the Arts & Weekend section of the Financial Times this week (Jan. 5, 2007) dealt with experimental economics. Experimental economists use the kinds of experiments run by psychologists and biologists to test out hypothesis and theories in economics and other branches of the social sciences. The most interesting part of the article was the idea of using the virtual world of online games as "a social-science supercollider." Anyone who has played some variant of Sims should see the potential in that type of experimental platform for economists.

The Genius of Finance -- Book Review of Fischer Black and the Revolutionary Idea of Finance

2006-12-24T08:01:00.000Z

In Fischer Black and the Revolutionary Idea of Finance, a biography of the legendary pioneer of quantitative finance by Perry Merhling, John C. Cox (finance professor at MIT) is quoted as saying that Fischer Black was "the only real genius I've ever met in finance." After reading this biography of the enigmatic and paradoxical life of Fischer Black, I wholeheartedly agree with Prof. Cox: Fischer Black was the genius of finance.

Fischer Black is best remembered for being the "Black" of the Black-Scholes option pricing model -- an intellectual achievement that, along with Modern Portfolio Theory and the Capital Asset Pricing Model (CAPM), heralded the birth of quantitative finance. But, as Perry Merhling masterfully reveals to the readers of his book, Fischer Black considered the Black-Scholes formula -- which earned Myron Scholes and Robert Merton Nobel Prizes (which would have been awarded to Fischer Black had he not died of cancer in 1995) -- to be a relatively minor component in his overall views of both the financial world and the world at large.

Unlike the vast majority of academics and practitioners, he was not slavishly loyal -- with the quasi-exception of his quixotic CAPM and equilibrium based philosophy, which cannot easily be pigeonhold into any stereotypical category -- to any particular school of thought or to any particular model, even ones' named after him. Instead, the framework with which he analyzed, and by which he even lived his all too brief life, was not any particular school of thought in finance but to finance itself. Fischer Black approached finance, not only as a science, but also as an art -- a way to express oneself and be creative.

To Fischer Black, finance was a port or a lighthouse in the storm; finance was a way to negotiate through the swirling currents and buffeting winds of risk and return. To Fischer (perhaps under the influence of one of his teachers, Harvard philosopher/logician W.V.O. Quine), finance was a language -- in fact, one of his proudest achievements was to create, for his students at MIT, a dictionary of finance (the definitions reflecting his unique views on finance) to provide a semantic schema for this language -- a way to formulate ideas and express them in a world full of uncertain gains and losses.

The book also reveals Fischer Black to have been a man of paradoxes and unconventionality. In his personal life, his daily routines were so invariant and downright boring that it would have been easy to predict what he had for lunch on a particular day (plain broiled fish and a baked potato with no butter), yet there were significant aspects of his life that were bohemian and extremely unconventional. He was capable of great generosity and humility, yet his lack of social graces could be off-putting even to those most closest to him. He was an academic that wound up as a partner at Goldman Sachs; he was a practitioner that did substantial research in finance on his own time and dime with no discernible intention to gain professional currency or glory.

The most ironic paradox was the fact that, although Fischer Black obtained a PhD in Applied Mathematics from Harvard, he could not solve the Black-Scholes stochastic differential equation using conventional methods from math and physics (he arrived at a solution through a kind of 'back-solving' method where Black and Scholes applied CAPM logic assuming a zero-beta security; Robert Merton later supplied a more straight-forward proof). This might be a sign to some that Fischer Black wasn't good at math (despite the PhD). I draw the opposite conclusion: If one views 'math' as being mostly about calculation or applying textbook methods in textbook ways, then Black wasn't a good mathematician. But, if one views mathematics as being, at heart, about applying logic and abstract thinking to creatively solve problems and prove propositions, then what Black did was brilliant mathematics -- arriving at an imaginative solution, using accessible and relatively simple tools at hand, to what was then a difficult conundrum that had stumped other brilliant thinkers.

Fischer Black's unconventional approach to life can best be summed up by his political preference during the 1980 presidential election. Rather than supporting Reagan, who his Chicago colleagues likely favored, or Carter, who his MIT colleagues would have been warm towards, Fischer supported the third party candidate, John Anderson!

His path to finance was, not surprisingly, an unconventional one. Fischer Black started his intellectual and professional career, not as an economist, but as a computer scientist and a technology consultant. His early career saw stints as a consultant at BBN, a firm that played a crucial role in the development of the Internet, and at Arthur D. Little.

His early career as a computer scientist (this was before there really was such a job description) had a lasting impact -- both in how he lived his life and in his approach to the the practice of finance when he latter joined Goldman Sachs -- on Fischer. Fischer's research in computer science was focused on artificial intelligence, but, whereas most AI researchers explicitly or implicitly centered their research on how machine intelligence could substitute for human intelligence, Fischer focused on the interaction between man and machine -- specifically, how machines could be used to enhance human intelligence. Fischer held onto to the idea that machines could enhance and supplement human intelligence and was skeptical that machines could truly replace man.

This led to another interesting paradox that was on display when Fischer joined the ranks of Goldman Sachs : On one hand, Fischer did not use the latest in computer technology for his personal work; his computer had a monochrome screen when color screens were widely available and probably did not have the latest in graphical user interfaces. In fact, he was (in)famous for relying on a paper-based filing system (whose only technological connection was that Fischer used a very simple organizational software called ThinkTank to catalogue the cards and notes) to memorialize his musings. Yet -- as Emanuel Derman, in his autobiography My Life as a Quant: Reflections on Physics and Finance, noted -- Fischer went to great lengths to insist on a user friendly interface for computerized valuation tools and trading systems for Goldman Sachs traders. Furthermore, Fischer had the foresight to predict automated trading systems and exchanges decades before they came into wide-spread use and acceptance.

It was at Arthur D. Little that he came into contact with CAPM and the pioneering work on quantitative finance done by Robert Samuelson, Harry Markowitz, William Sharpe, and, most significantly for Fischer, Jack Treynor. It was CAPM, and the closely related idea that prices tend toward equilibrium, that served as Fischer Black's map and compass on his many adventures in finance and economics as a professor of finance at the University of Chicago and at MIT as well as at Goldman Sachs.

In the field of finance, Fischer's contributions and musings are too numerous to recount here, but he made important contributions (or could have if some of his thoughts had been more widely circulated) to almost every field of finance, including financial and managerial accounting, tax accounting and law, corporate finance, international finance, and investment management. In direct opposition to the 'efficient market hypothesis' school of thought, Fischer was one of the first to recognize the influence of noise traders on financial markets. He went so far as to argue that the Black-Scholes model -- which initially would have provided 'signals' (valuable information) in the marketplace -- had contributed to some of the increasing noise in the financial markets. He further demonstrated an ability to sacrifice ego for the sake of advancing knowledge and practice when, at Goldman Sachs, he encouraged the use of discrete, tree-based option pricing models by John Cox, Stephen Ross, and Mark Rubenstein (with some inspiration by William Sharpe) over the Black-Scholes-Merton model because the tree model was more flexible.

Whereas his contributions to finance, including his challenge to conventional wisdom, was, at the very least, met with general acceptance by the financial community, Fischer's forays into other parts of economics -- especially macroeconomics -- were met with a great deal of skepticism if not downright hostility. His views of the business cycle and monetary theory were considered to be almost blasphemous by some -- his 'monetary theory' basically did away with money altogether! (At least, the convention notions of money.) Fischer's theories of macroeconomics were based on his quixotic views of CAPM and equilibrium and did not fit in either with the Keynesian (or neo-Keynesian) or Monetarist camps; Fischer's views could best be called the 'finance theory of macroeconomic business cycles.' In fact, he had been a professor at the 'holy cities' of both camps (Chicago for Monetarists and MIT for neo-Keynesians) and made little headway with either group in converting them to his ideas. As Perry Mehrling correctly points out, time seems to be on Fischer's side, and, as recent trends in the awarding of Nobel prizes to macroeconomists with views similar to Fischer's seem to suggest, Fischer's views may step out of the intellectual wilderness and become mainstream views in the near future.

In both his forays into finance and economics, as well as in aspects of his personal life, the idea of equilibrium, which Fischer saw as being at the core of his CAPM-based philosophy of life, was of critical importance to Fischer Black both intellectually and as a man. But his approach to economic, financial, and other types of equilibrium was, as in other aspects of his life, paradoxical. On one hand, his devotion and laser-like focus on general equilibrium would have put even the most ardent Chicago-school economist to shame. Yet, Fischer's idea of equilibrium was not the static or smooth one that is typical of economists of any school; Fischer inherently viewed equilibrium as being dynamic and jumpy.

To Fischer Black, equilibrium was a goal of life and not necessarily a fixed state of being. Rather than staying in place or being completely aimless, Prices will move from equilibrium towards a new equilibrium. In other words, equilibria serve as attractors to prices but they were by no means the unchanging and unerring entities as they were in the minds of many economists. Moreover, the idea of equilibrium, e.g., finding the right balance between risk and return, was more of a guiding philosophy and an analytical framework to Fischer rather than some unbending rule that one simple-mindedly tied oneself to.

Fischer's more flexible attitude toward equilibrium allowed him take the right kinds and amounts of risks. Fischer took a great deal of intellectual risks with his research because he, rightly, saw that the returns to him were well worth the risk. Fischer, however, refused to take less-than-wise financial risks. For example, although he had been offered a position with a great deal of financial benefits to take part in the mis-adventure of LTCM -- an offer that both of his option pricing colleagues, Myron Scholes and Robert Merton, took to their regret -- Fischer rejected their offers. In Fischer's mind, LTCM was "loading up on risk." It turned out, after his death, that he was absolutely correct.

Fischer's willingness to challenge conventional wisdom (and foolishness) was perhaps best displayed in his famous "Fifty Questions" in finance courses at Chicago and MIT. There he was in his element; like a master painter working at a canvas or a poet tapping away at a typewriter, Fischer Black used his classes -- with the aid of his "Fischer Black's Glossary for Finance" -- to explore the language of finance. The questions were usually the same from class to class, but the answers were often radically different. Such is the price of genius.

Swarm Marketing: More Tyranny of the Power Law?

2006-12-14T00:06:00.000Z

A while ago I read a couple of articles on swarm intelligence, social network theory, and marketing. One of the articles was in The Economist, Swarming the shelves (Nov. 9, 2006), and the other was a Harvard Business Review piece co-written by Columbia mathematical sociologist Duncan J. Watts and McKinsey consultant Steve Hasker, Marketing in an Unpredictable World (Sep. 2006). I wanted to very briefly analyze these two articles because I think they: (a) are interesting bits of research on their own, and (b) they become even more fascinating in light of the long tail and a previous blog piece I wrote, Tyranny of the Power Law (and Why We Should Become Eclectic).

The Economist piece discusses a marketing strategy developed by two Florida Institute of Technology computer scientists for use in supermarkets and other retailers. Taking advantage of radio frequency identification tags that are increasingly getting embedded into consumer products, the researchers propose to use that technology, along with wi-fi screen/scanner included with every shopping cart, to inform customers about how many other consumers choose that particular product.

This scheme is basically a take off on an old marketing trick, 'bandwagon effect,' updated with the latest in social network analysis and mobile technology. The idea is that consumers will tend to 'herd' toward particular products because it was popular with other consumers; with up-to-date technology, consumers can now be more rapidly informed of what choices other consumers made. Think of the 'cool kids' in high school becoming more popular because everyone was informed they were popular.

The Economist piece also makes a passing reference to the research done at Columbia University that is written up in a popular format in the Harvard Business Review article. The research, published in Science as Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market (311:854-856, Feb. 10, 2006), by Salganik, Dodds, and Watts involved a web-based experiment where the researchers created a market for downloadable music. They used this experimental market to see the influence of social influence on consumer choices and the predictability of a product's success. They found that "increasing the strength of social influence increased both inequality and unpredictability of success." In other words, increasing the influence that people have on each other -- e.g., by informing consumers of what products are popular -- will tend to make popular products more popular and widen the gap between them and less popular products as well as make it harder to predict beforehand which products will turn out to become popular.

All of this should sound familiar to those of us familiar with things like smart mobs, the business/pop-science book The Wisdom of Crowds, and the power law; the crowd tends to know better so we should go along with the crowd. This stands in contrast to the ideas put forward in the book The Long Tail and in my blog post Tyranny of the Power Law (and Why We Should Become Eclectic). In fact, Watts and Hasker directly challenge and contradict the long tail theory -- that technological innovations should lead to a wider and eclectic assortment of choices for consumers -- in their HBR piece.

As I made it known in the "Tyranny of the Power Law" blog post, I have serious misgivings about the type of world that Messrs Watts, Hasker, et al. envision. Yes, it's nice and helpful to know what other people are buying. As I made clear in my previous blog post, I don't disagree with the idea that crowds are sometimes wise. But are they always wise? And, as I tried to philosophically dissect, even if people tend to go along with the crowd and make popular things or people more popular, does that mean that such a mentality is an unalloyed good or is something we should encourage as a normative policy prescription?

Lemmings also follow the herd ... down ravines and to their doom. Crowds can be daft and mad and following them has often led to some of the most foolish and catastrophic incidents in history. As the Science piece points out, the network effects of social influence -- which can be fitted with a power law distribution -- can cause a serious disconnect between quality and ultimate success.

In that experiment, the 'best' (a quality which was determined by comparing the social influence conditions to the placebo/independent condition) songs, while doing well on average, did not always succeed as one might have expected and, in terms of market share, had the most unpredictable outcomes. In other words, at least for the music download market experiment, there was at least some substantive detachment between quality and success.

In real life, as opposed to artificial experiments, we can -- and have seen -- even greater disassociation between quality and success. The best products and people don't always get the success they deserve. That is, at least in part, due to the 'tyranny of the power law': Some products, services, people, and organizations get a leg up (sometimes, unfairly) and their pre-ordained success gets reinforced by social structures that are rigged to keep it that way ... meritocracy be damned. It's like high school, the cool kids weren't always the smartest or the most talented kids. The cool kids were cool because ... well, they were cool to begin with. That might be okay for teenagers, but is that any way we want to run a country, encourage culture, promote an educated populace, and run a business?

Pop Culture & Hedge Funds

2006-12-08T23:40:00.000Z

The New York Times has an article today on how hedge funds are getting 'name checked' in various outlets of pop culture: Culturally, Hedge Funds Go Public (Dec 8, 2006). From soap operas to a "for Dummies" book, and even a shoe (by Kenneth Cole) named after it, hedge funds are going mainstream.

IMHO, all of that probably means that there will be a major crash and/or scandal in the hedge fund industry (beyond what we have already had) very soon ;)

Goldman Sachs' Hedge Fund Clone

2006-12-03T21:17:00.000Z

Goldman Sachs, one of the most prestigious investment banks in the financial industry, is setting up a hedge fund replication tool (or hedge fund 'cloning' tool) -- which it calls the Absolute Return Tracker index (ART) -- that may usher in a new era of even greater competition in the hedge fund industry. You can read about it in today's Financial Times.

This announcement is closely tied to a previous blog posting I did -- The Econophysics Blog: Hedge Funds & Minding One's Pennies -- about how finance academics at MIT and other schools are attempting to create an intellectual foundation for replicating the performance characteristics of hedge funds at lower costs and using more accessible financial instruments.

New Scientist's Interview of Nassim Taleb: Life is Unpredicatble - Get Used to It

2006-11-30T08:19:00.000Z

Nassim Nicholas Taleb has posted an interview that the New Scientist did with him in July: Life is unpredictable - get used to it (Michael Bond, July 1, 2006). In the article, Taleb discussed what he calls "type two" randomness -- which he has also referred to, in the past, as "wild randomness" -- or "black swans." "Type two" randomness (or "wild randomness" or "black swans") are those unpredictable and extreme events that have 'catastrophic' -- either for good or for ill -- impacts on society and nature. Unlike "type one" randomness -- that which we encounter in such textbook favorites like the bell curve (or the so-called 'normal' distribution) or flipping of coins -- "black swans" are not well-behaved enough for us to 'manage' in the conventional ways with which we try to analyze and manage uncertainty.

Nassim Taleb will outline his views in greater detail in his forthcoming book, The Black Swan. If it is anything remotely as mind-blowing as his previous book, Fooled by Randomness, I'm definitely looking forward to reading it.

More on China's Financial Sector

2006-11-17T18:27:00.000Z

This is a follow up to my previous blog post The Econophysics Blog: China's Inefficient Securities Markets.

The New York Times had an article this Wednesday (Nov. 15, 2006) where a former risk adviser to a major Chinese bank revealed that the number of bad loans (NPLs or non-performing loans) was much much worse than what is revealed in the bank's publicly available ledgers: Rare Look at China's Burdened Banks. In the case of China Construction Bank (the bank that fired the risk adviser), "up to $3 billion in bad loans might have been intentionally hidden from outside auditors, just months before the bank's first sale of stock to public investors."

The November 2006 issue of The National Bureau of Economic Research (NBER) Digest has an article describing research asking the question Will Super-High Chinese Growth Continue?. According to the article, China's Foreign Invested Enterprises (FIEs) have a disproportionate impact on the prospects for China continuing its torid pace of economic growth. The research concludes that if FDI (Foreign Direct Investment) levels drop off -- FDI being of critical importance to FIEs -- China's current economic growth rates will probably not be sustainable.

Economic Theory of Art & My Wittgensteinian Thoughts on It

2006-11-16T00:33:00.000Z

David Leonhardt has another one of his reliably fascinating articles in the New York Times today (Nov. 15, 2006): The Art of Pricing Great Art. It profiles Prof. David W. Galenson, an economist at the University of Chicago. He has become famous -- and infamous in some circles -- for developing what amounts to an economic theory of great art or artistic genius.

Prof. Galenson's theory, in a nutshell, divides great artists (btw, he has extended his theories to non-visual artists, including writers) into two basic categories (based on statistical analysis and economic reasoning): "conceptual innovators" (or "conceptualists"), like Gaugin, Picasso, and Van Gogh, who tend to do their best work when they are young and tend to produce their works at a rapid clip; and "late bloomers" (or "experimentalists"), like Cezanne, Jackson Pollock, and Beethoven, who tend to arrive at their innovations gradually (experimentally) and often make major contributions later in life. To people who are familiar with the 'life cycle theory of consumption and savings' from economics, Prof. Galenson's 'grand unified theory' of art should sound familiar and, perhaps, comforting.

David Leonhardt's article is generally favorable towards Prof. Galenson's approach. Others who are 'pro' Galenson include Malcolm Gladwell of The New Yorker who gave a lecture at Columbia University on Prof. Galenson's theory entitled Age Before Beauty (audio from that lecture can be heard from that page). Wired Magazine has a detailed article on Prof. Galenson (by Daniel Pink) titled What Kind of Genius Are You? (July 2006).

Not surprisingly -- considering the fact that Prof. Galenson is encroaching into a territory that isn't typically considered to be math friendly -- the economic theory of art has taken quite a bit of flack from art experts. According to Prof. Galenson, "The art historians and art critics won't look at my work. They just assume I'm an idiot."

The intensity of the opposition is best illustrated by the treatment that Malcolm Gladwell, a respected staff writer and editor for The New Yorker, received from his magazine. Mr. Gladwell -- who I consider to be a genius (conceptualist or experimentalist???) in the world of non-fiction writing and who is not accustomed to rejection -- received his first rejection from The New Yorker when he tried to submit an article about Prof. Galenson's theories ... a rare, triple sigma event indeed!

Readers of this blog may expect that I would give my unqualified support to Prof. Galenson's views. Unfortunately, I will have to disappoint expectations somewhat. It's not that I'm not fascinated by nor approve of Prof. Galenson's novel and creative approach in applying quantitative tools to seemingly unquantifiable issues (I am very fascinated and I wholeheartedly approve). It's just that I think fans of Prof. Galenson are being too optimistic about his theories.

For example, the Times article draws analogies comparing the Galensonian theory of art to other attempts at 'quantitative colonization' like evidence-based medicine (i.e., data driven medicine) and sabermetrics (applying mathematical statistics to baseball data). I think these analogies are imperfect because art -- unlike human biology / medicine and baseball statistics -- really does involve things that are unquantifiable and it is precisely those unquantifiable factors that are often the key factors (especially with 'great' art) that distinguishes art, music, and creative writing from run-of-the-mill drawings & figures, noise, and jumbles of words.

I want to make it clear that I'm not opposed to Prof. Galenson's (or anyone else's) attempts at quantitatively analyzing art (or other endeavors that have at their heart unquantifiable factors). In fact, I encourage trying to take the positivist (empirical and/or deductive) 'project' as far as possible ... but no farther (i.e., don't over do it!). In this context, I'm reminded of what Ludwig Wittgenstein said about his Tractatus Logico-Philosophicus -- perhaps in response to positivist 'fans' of the Tractatus who erroneously thought that Wittgenstein was elevating the verifiable (i.e., quantifiable) to the exclusion of the unverifiable (i.e., unquantifiable) -- "My work consists of two parts: the one presented here plus all that I have not written. And it is precisely this second part that is the important one."

In keeping with Wittgenstein, I believe that we can (and should) analyze the quantitative aspects of art but it is the unquantitative aspects of art that may well be the more important of the two.

Glenn Gould and Commodity Prices

2006-11-10T02:38:00.000Z

Now that the elections are over, oil prices are starting to rise ;-) But let me take you back to the not so distant past ...

September 2006, saw the biggest one month decline in gas prices (down 22%) in recorded history. By October 2006, it was clear that the 'roll yield' -- the returns on holding a futures contract conditioned on spot prices being higher than past futures prices -- turned negative (as of mid-October, -13.35%), costing investors in futures contracts millions in expected profits (Buttonwood, Roll over: Overcrowding is unbalancing the world of commodities, The Economist, Oct. 12, 2006).

One has to keep in mind that this mini-crash (or, perhaps, a full blown crash) in oil prices was -- outside of a few 'Jeremiahs' -- totally unexpected. If we went back slightly further in time, say March or April of 2006, and suggested to a commodities trader that oil prices would drop 22% by the Fall, we would've been openly laughed at. Even as late as mid-August, the notion that there was a 'bubble' in oil prices ripe to be punctured by a crash was dismissed by many experts (see, e.g., Norm Alster, Is a Futures Stampede Keeping Oil Prices High?", New York Times, Aug. 13, 2006, which discusses Ben Dell's prescient report, in July, exposing how the increase in speculative interest in oil had created a bubble that was ready to burst). All of this brings us to Glenn Gould.

For readers of this blog with sophisticated palates (and ears), they may have wondered what Glenn Gould possibly has to do with commodity prices (e.g., the price of oil). Glenn Gould -- besides being a great classical piano player best known for his interpretations of Johann Sebastian Bach -- was an all-around genius who made fascinating contributions to radio broadcasting, studio recording techniques, and the philosophy of music. It also turns out that he was a successful financial speculator.

In the 1993 movie (part docu-drama, part documentary), Thirty Two Short Films About Glenn Gould, one of the 'short films' -- titled "The Tip" -- retells the story of how Glenn Gould profited by betting against rising oil prices during the 1970s oil embargo and energy crises. In that film sequence, to the frenetic strains of Glenn Gould's take on Prokofiev's Precipitato from Sonata #7, we see financial traders riding the wave of rising oil prices justifying their decisions with lines like, "Play it safe. I'm sticking with the big one, oil that is ... Black gold ... Texas tea."

As we see market herding unfolding on screen, we see a strikingly different scene taking place in a booth in a plush Toronto restaurant. In stark contrast to the manic energy of financial trading rooms, Glenn Gould is shown sitting placidly at his usual table in the Fairmont Royal York Hotel Restaurant. Calling his broker, Glenn Gould tells him to sell oil and buy the stock of an obscure oil exploration company -- a contrarian bet that oil prices would drop. By the end of "The Tip," we see that Gould's bet is vindicated; oil prices and stock prices dependent on rising oil prices crashed while the price of the stock that Gould bet on rose. This prompted Gould's broker to tell him, "Maybe you should give up playing the piano altogether and just play the market. That's right, a virtuoso."

The lesson we can take away from all of this is that -- no matter how sure a thing the 'sure thing' seems to be at the time -- a crash can happen in the most unexpected ways and at the most unexpected times. The risk of crashes are particularly high when -- as argued by both the Buttonwood piece (which, when I read it, called to my mind the El Farol bar problem) and by the econophysicist, Didier Sornette -- herding takes place in the financial markets. In those scenarios, Gould-ian virtuosity calls for going against the tide.

Book Reviews: Predicting Presidential Elections and Other Things & Freakonomics (Revised Ed.)

2006-11-08T00:40:00.000Z

In honor of Election Day (Tuesday, Nov. 7, 2006) across the US, I am posting a short book review of Ray Fair's Predicting Presidential Elections and Other Things along with an even briefer review of Steven Levitt & Stephen Dubner's Freakonomics (Revised Edition).

Prof. Ray Fair, an economist at Yale, originally intended to title his book either as "What Can Econometricians Do?" or "Econometrics Made Easy." As he retells in the Acknowledgments section, his kids talked him out of those titles. That's a shame because those titles are actually better descriptions of what Predicting Presidential Elections is really about: What creative econometrics can reveal about the world told in an accessible manner.

That is not to say that Prof. Fair's book doesn't live up to its title; it does. Most of the first half of the book carefully explains how he came up with an econometric model to explain the results of presidential elections. He then uses this model to predict the results of the 2000 and 2004 elections. (He has subsequently made predictions for presidential elections since then at his website.)

But the book doesn't stop there. Prof. Fair also discusses econometric models of extramairtal affairs, college grades & class attendance, performance in marathons (Prof. Fair is an amateur runner), more traditional economic topics like interest rate & inflation, and a very interesting chapter on the econometric valuation of fine wines. This is econometrics at its best; taking fairly basic tools from econometrics and applying them creatively to explore interesting questions.

What one gets out of Ray Fair's book is a sense that one has really learned econometrics. The book does a good and accessible job of explaining what statistical regression analysis (the cornerstone of econometrics) is as well as t-tests for significance and other fundamental statistical issues.

Another book that explores the creative possibilities of econometrics is Freakonomics, a surprising best-seller. Much has already been written about this book -- most of it pro rather than con -- so I don't have much to add. I will note that the 'Revised Edition' has just been published. It is basically the same as the original except: (a) some parts have been re-written to incorporate some new facts that have been brought to the authors' attention, and (b) some of the more interesting posts from the popular Freakonomics Blog have been included in book form.

I have one mild criticism of Freakonomics in comparison with Ray Fair's book: Unlike Prof. Fair's book, Levitt & Dubner's book doesn't attempt to give the reader a sense of having learned what econometrics is even though that is what is at the heart of the book. There is little or no mention of regression coefficients, statistical significance tests, etc. In fact, there is hardly a number in that book (unless you count the page numbers)!

Perhaps Levitt & Dubner were heeding the apocryphal advice rumoured to have been given to physicist Stephen Hawking that there is some proportional drop in sales with every mathematical equation that is added. But, surely it wouldn't have harmed sales of this best-seller too greatly if just one or two mathematical expressions were thrown in for intellectual credibility's sake? Levitt & Dubner can hardly claim that it is too difficult to write an accessible guide to econometrics ... Ray Fair has proved otherwise with his fine book, which is a kind of Freakonomics with the math (in digestable doses) included.

It's a shame that readers of Freakonomics -- unlike readers of Predicting Presidential Elections and Other Things -- don't get a sense that they've learned at least a bit about econometrics since Steven Levitt is one of of the most (if not the most) creative econometricians around. My advice to readers of Freakonomics is that -- if they want to take the next small, baby step towards understanding the tools that Prof. Levitt used to arrive at his interesting observations about the world -- they read Prof. Fair's book (perhaps along with Philip Hans Franses' A Concise Introduction to Econometrics: An Intuitive Guide) for a relatively easy introduction to what econometricians can do.

Hedge Funds & Minding One's Pennies

2006-11-01T19:54:00.000Z

There is an old adage that basically goes like this: 'Mind your pennies, and your dollars will mind themselves.' ('Pounds' instead of 'dollars' if you're in the UK.) Investors in hedge funds would do well to keep that maxim in mind. After all, even if hedge funds can deliver the stellar returns they trumpet (despite the mounting empirical evidence that the belief in hedge fund out-performance tends to be exaggerated), the high costs associated with investing in hedge funds should provide investors with incentives to look for cheaper alternatives.

According to the Buttonwood column in The Economist, Send in the clones: A cheap alternative to hedge funds (Oct. 26, 2006), finance scholars have come up with ways to create cheaper, 'knock-off' copies of more expensive hedge funds. For example, MIT's Andrew Lo and Jasmina Hasanhodzic have written a research paper, Can Hedge-Fund Returns Be Replicated?: The Linear Case, that "raises the possibility of creating passive replicating portfolios or clones using liquid exchange-traded instruments that provide similar risk exposures at lower cost and with greater transparency." They do so by using econometric techniques to identify six factors that are closely associated with hedge funds' expected returns and volatility, and using those findings to create back-tested portfolios that 'clone' hedge funds.

Besides the theoretically lower costs of these hedge fund 'clones,' an additional benefit is that they use off-the-shelf financial instruments and assets instead of the less accessible tactics and products that hedge funds often use. Therefore, in theory, average investors would have easier access to these more liquid exchange-traded assets and that could make it easier to clone hedge funds without having to rely on more exotic instruments.

I have to admit, however, that I'm a bit skeptical of the promises of hedge fund 'cloning' (I don't even like that term since it's a bad analogy to biology since these cheaper alternatives would not be exact 'genetic' copies of the originals). Sure, I like the theoretical possibilites of having cheaper investment vehicles that utilize more accessible financial assets and strategies. The problem is that I'm not sure whether theory will be translated properly into practice. The kind of techniques that Prof. Lo and others who are cited in the Buttonwood column use to 'clone' hedge funds require algorithms and skill sets that are at least as -- and, probably, more -- sophisticated than the methods utilized by hedge funds themselves. That alone would likely mean that, rather than run-of-the-mill punters, sophisticated and deep-pocketed investors -- such as institutional investors and investment firms (including hedge funds themselves) -- would be able to utilize these strategies. So if the heavy hitters are best positioned to use these 'cloning' techniques, why would the costs go down when they have little incentives to lower the costs and the techniques themselves entail high human capital costs?

On a lighter note, I noticed a blog post on the New York Times' DealBook, Amaranth's Other Casualty: The Cabbies, that details how a taxi company's business was hurt by the blow up of a hedge fund. This is reminiscent of my last blog post on Daylight Savings Time and network effects. Apparently, the hedge fund world also has coordination or network effects (or externalities) on other parts of society and the economy. Relatively speaking, the billions of dollars of trades that hedge funds like Amaranth were dealing in make the fat fares of Connecticut cabbies look like pennies compared to dollars. In this case, a hedge fund not minding their 'dollars,' caused cabbies to lose out on 'pennies.'

Daylight Savings Time and Network Effects

2006-10-29T10:01:00.000Z

Daylight Savings Time is coming to an end in the US. (Other parts of the world follow similar time conventions; e.g., 'British Summer Time' (BST) in the UK.) Appropriately enough, Tim Hartford, aka 'the Undercover Economist,' in his weekend column in the Financial Times (UK) wrote about the economics of Daylight Savings Time: Undercover Economist: Think inside the box (Oct. 27, 2006).

Specifically, he wrote about what economists call network effects (or network externalities) and what affects, if any, the twice-a-year change to our clocks has on the coordination of both economic and social behavior. One possible network externality of the DST is that one type of profession needing to wake up one hour later (or earlier) will have a feedback effect that causes people in seemingly unrelated jobs to have to coordinate their work schedules even though they have no direct reason for doing so. An example that Tim Hartford used was a financial trader or analyst on the West Coast of the US having to adjust to -- not only the East Coast time at which the NYSE operates on -- the switch caused by the start or ending of DST.

There is an additional complication caused by the fact that some parts of the US (and other countries) don't recognize DST (or its equivalent); e.g., Arizona. Also factoring in regions at the borders of time zones and large time gaps between regions in large countries (e.g., 3 hour time difference between the coasts of the continental US).

Economic research seems to indicate that there are network effects to socio-economic coordination caused by timing conventions within and between regions. The somewhat surprising finding is that -- rather than the timing conventions themselves -- it is often television schedules (which both follow and have their own peculiar timing conventions) that set our social and economic clocks.

Three economists, Daniel Hamermesh, Caitlin Knowles Myers, and Mark Pocock, have devised a way to find out how important these co-ordination effects really are. One of their tools is based on a historical relic: the fact that television schedules in the US vary by time zone. This practice originated in the 1920s, when the Eastern and Central time zones received simultaneous live radio broadcasts, the Central time zone broadcast being an hour earlier on the clock. The sparsely populated Mountain and Pacific time zones had to listen to repeats instead. For no other reason than pure tradition, prime time evening shows screen at 10pm Eastern and Pacific, 9pm Central and Mountain.

....

Rather depressingly, late-night talkshow host David Letterman outshines the sun in his effect on what people are doing. Push the television schedules an hour later and 5 per cent of people will be watching television later - nearly a third of those actually watching the television. But if sunset is an hour later (because the individual is at the western end of a time zone) only half of 1 per cent of people will watch later television.

That itself might not be surprising, but the effect spills over on to sleeping patterns: the television, more than the sunrise, determines when people get up in the morning. It even governs the behaviour of people who don’t watch much television, since they need to be co-ordinated with everyone else. It seems that co-ordination with other human beings is more important than official time, or even than sunlight itself.

China's Inefficient Securities Markets

2006-10-24T22:28:00.000+01:00

Over the last few years, there has been a great deal of excitement and interest about China. Not surprisingly, this also extends to the world of finance and business. For good or for ill (more often than not, the later), people have dreamed about the economic prospects of investing in China.

Despite the hoopla and the enthusiasm, however, it's clear that China's financial markets have to develop further before they are can live up to lofty expectations. The Economist magazine recently had two articles that highlights the perils of expecting too much out of China's securities markets and financial system.

The first article, Imperfect markets: China's different share classes damage its own prospects, points out the fact that share prices for the same publicly traded Chinese companies are different depending on the market in which those shares (again, for the very same company) are traded. Larger or more recognizable companies tend to have higher prices outside of mainland China (in Hong Kong, etc.) than they do on domestic stock exchanges (in Shanghai and Shenzhen). Smaller companies reverse this trend: they tend to trade at a premium on domestic exchanges relative to their valuations outside of the mainland.

These distorted prices -- where what is theoretically the same thing are priced higher in one place and lower in another -- violates the Efficient Market Hypothesis (EMH). According to EMH, arbitrage should eliminate these price discrepencies in short order. The distorted pricing of Chinese stocks violate the central tenet of economic price theory: Prices should be the ideal mechanism for conveying economic information about the good, service, or asset in question. When prices don't conform to the 'one price' principle, it makes the information revelation and exchange process -- via prices -- less efficient and less useful.

So why haven't these prices been arbitraged back towards some equilibrium price? The answer, as the article suggests, is that it is difficult to arbitrage Chinese securities because of institutional limitations. (To be fair, even with the limitations, there has been a narrowing of the gap between prices for companies traded in both Hong Kong and on mainland exchanges in Shanghai or Shenzhen.)

Chinese companies tend to issue shares using separate share classes with differing rights and restrictions. That, along with the reluctance of the government to cede authority over corporate governance matters in certain key industries, create legal risks that contribute to the pricing disparities. Furthermore, until recently, very few derivatives products have been allowed; derivatives that take into account share class differences and cross-border issues would allow traders to arbitrage away many of the distortions that now exist.

Despite its title, the second Economist article that caught my interest, Profits and prophecies: Chinese companies earn higher returns than is commonly claimed, also deals with the still developing nature of investing in China. This article highlights the debate between those optimistic about China's business prospects -- a couple of World Bank economists and Ms. Hong Liang of Goldman Sachs -- versus those who are more skeptical -- Mr. Weijian Shan, an economist and private equity investor for Newbridge, and others.

The optimists point out that both returns on capital and returns on equity have risen at a more than respectable rate for Chinese companies. They also cite reasons for optimism regarding how Chinese companies are financing their business investments. One of the fears that people have for China's economy is that there exists a pile of bad or dodgy debts that may collapse one day -- bringing down with it much of China's recent economic advancements. The optimists suggest that Chinese firms are increasingly relying on internal financing (investing out of their own cashflows and retained earnings) rather than bank loans.

Skeptics, like Weijian Shan (who I have a great deal of respect for; you can read a profile of him by clicking here), point out that costs -- commodity prices, labor costs, etc. -- are rising and China doesn't have the pricing power (i.e., goods are manufactured and bought from Chinese companies because of low prices) to offset those rising costs, profit margins are falling and may continue to fall. Furthermore, the skeptics point out that the optimists are naive in thinking that whatever move away from bank financing that may exist would solve the debt/insolvency crisis that could happen at any time in the near future.

[I ignore the issue of the rather sketchy nature of economic statistics and accounting in China. The optimists are well aware of the issue and do the best they can to deal with that (e.g., they look at return on equity of companies whose shares are traded outside of China).]

Without taking sides on this debate (since both sides make meritorious arguments), I think it's safe to say that a big part of the problem is that China doesn't have fully developed securities markets. Besides lacking full-featured derivatives markets (which is not necessarily a bad thing considering the stage of economic, regulatory, and legal development China is currently in), China doesn't really even have a mature bond market -- something so basic that we in the 'West' often take it for granted: As the article points out, corporate bonds are only 4% of China's GDP while they are over a 100% of U.S. GDP.

Having fully developed securities markets (debt markets, stock markets without byzantine multiple class divisions, etc.) would make the debates about China's economy and financial system much more fruitful. Although I doubt that what I'm proposing would fully solve all the thorny problems that exist, at the very least we would able to better measure -- through more efficient pricing -- the true condition of China's economy and that would, hopefully, allow policymakers, investors, and managers to better tackle the problems that exist.

PS: A brief sidenote on some econometric issues related to the second Economist article. The article points out that the optimists believe that improvements in what economists call 'total factor productivity' (or TFP) will offset high commodity costs, rising wages, and (although the Economist article doesn't mention this) demographic risks, that affect the inputs into China's manufacturing sector. The otherwise excellent Economist article neglected to mention the skeptics' potential objections to the increasing productivity argument. Namely, productivity gains (and losses) are difficult to measure and their affects, even if they could be properly gauged, is highly uncertain. So it's not clear to me that, as the article seems to suggest, TFP gains (even if they are real) would fully offset the risks.

Randomness & the 'Ludic Fallacy' on Numb3rs

2006-10-21T22:05:00.000+01:00

I'm a big fan of the CBS TV show, Numb3rs, where the FBI recruits a mathematics professor (and his colleagues) to help solve crimes. Every week (it's usually shown on Friday evenings), there are some interesting bits of math concepts and trivial that I find to be educational and informative.

Yesterday's episode (Oct. 21, 2006) had the following storyline: There are a series of freeway attacks in Los Angeles -- some involving rifle shots, others involving bricks or other objects thrown onto windshields. Are they random attacks or is there a particular individual (or individuals) who are deliberately carrying out the attacks?

'Charlie Epps' -- the math professor who consults with the FBI -- initially concludes that the attacks are random (a reasonable conclusion factoring in the fact that it involves Los Angeles roads) and dismisses any concern that there might be a pattern to these attacks as the hopelessly untrained musings of the mathematically challenged. 'Megan Reeves' -- one of the seemingly mathematically challenged FBI agents -- comes to a rather different conclusion. She begins to wonder out loud whether or not the attacks are "too random" to be actually random.

To his credit, Prof. Epps eventually comes to agree with Agent Reeves. The process by which Prof. Epps initially dismisses challenges to his expert opinion and then comes to a more humbler change of heart says a lot about how mathematicians, statisticians, and similar quantitative professionals have notions about randomness that are even more flawed than the common sense ideas of the mathematically challenged laymen that the pros regularly (to be fair, usually correctly) deride. I also think the storyline of the show is a great object lesson on the intellectually challenging nature of randomness.

Prof. Epps explains his initial conclusion of random attacks by drawing an analogy to the shuffle mode on IPods. According to the Epps character on the show, the shuffle mode has an algorithm that randomizes the selection of songs that your IPod will deliver to your ears. Thus, Prof. Epps asserts, any 'pattern' you discern from what songs your IPod selects is illusory. (Both the show and this blog post will ignore the fact that such algorithms are psuedo-random, at best, and not truly random since, by definition, algorithms are deterministic.)

Agent Reeves objects by wondering whether or not the supposed non-pattern of attacks seems too random. She points out that, compared to each other, none of the attacks follow a similar m.o. (modus operandi); i.e., in terms of methodology, the attacks are never repeated and/or clustered. While that may sound like it bolsters the case for random attacks, it is actually suspicious because -- as the very beginning of the show (where Prof. Epps makes this point to a class on probability theory) points out -- truly random series of events should have some clustering and/or repeats. In fact, one way people try to counterfeit randomness is by making events seem too evenly spread out from one another.

Prof. Epps realizes this error and corrects his IPod shuffle analogy: It turns out the IPod shuffle algorithm is not an ideal (psuedo-) randomizing algorithm because it does not repeat songs already played until all the songs on the playlist have been played (so, at best, it's like a well-shuffled deck in a hand of poker). So he winds up conceding that Megan Reeves was right to think that attacks were indeed "too random" to be random.

One of the fallacies that the Prof. Epps character committed was what Nassim Nicholas Taleb has called the "Ludic Fallacy" (to my knowledge, he first coined and defined this term in his forward to Aaron Brown's The Poker Face of Wall Street). As I understand it, the Ludic Fallacy refers to the unfortunate habit of many quantitative professionals (statistics and economics professors, Wall Street traders, management consultants, government technocrats, etc.) to over-simplify the nature of randomness and chance by making mistaken analogies to games ('ludic' -- of or relating to games or play -- comes from the Latin ludus -- game or play) of chance.

One of the several reasons why the Ludic Fallacy is a fallacy is because most games of chance (with the notable exception of poker, which -- as Nassim Taleb hints at -- is more reflective of real-life "wild" randomness because that game has major strategic and tactical components to it that is mashed up with the quasi-stochastic element of a shuffled deck) have probability distributions that are too neatly defined and managed to accurately reflect the real-life 'wildness' of randomness as we experience it in the real world. For example, the predicted results of those games of chance have nice, well-defined statistical 'moments' -- like mean (or average) and variance (or standard deviation) -- that are useful in classrooms or on hedge fund prospectuses but may not be as meaningful in our day-to-day lives (as this blog, NNT, and others have pointed out in the past).

Prof. Epps' analogy to the IPod shuffle mode was a ludic fallacy since the shuffle mode is essentially the same problem as shuffling a deck of cards (an ideal shuffled playlist of music on an IPod is analogous to the 'well-shuffled deck' problem in blackjack, poker, and combinatorics). The well-meaning TV character drew a bad analogy to a game of chance -- shuffled music on an IPod -- to explain something much more complicated to be shoe-horned into the IPod shuffle story. Sadly, it's not just TV characters that fall for this fallacy; statistics classes and investment sales pitches are filled with this sort of fallacy.

I don't want to be misunderstood. I can't speak for Mr. Taleb, but I want to make it clear that drawing analogies to even the simplest of games of chance (like flipping coins or throwing dice) can be -- and, in fact, are -- good ways of explaining and exploring the nature of randomness and probability. What I object to is the indiscriminate use of these stories where the storyteller is not thoughtful or informed enough to understand the benefits and limits of using such games in 'philosophical experiments.'

My bottom-line is: It's okay to draw analogies to games of chance when dealing with randomness. Just be sure to think through the true nature -- both the potential and the limits -- of those games of chance and chance itself.

One final note ... there is another side to the coin of how even math pros make mistakes about randomness. I've spent (and the TV show spent) most of the time talking about the nature of the underlying (and, usually, unknown) probability function. The other side of the coin of randomness fallacies is the idea of magnitude or impact of making the wrong predictions. As Charlie Epps' father (ably played by Judd Hirsch) pointed out to his son -- as the math 'genius' was telling story after story about card games, lotteries, and how all that makes it unlikely that dear old dad wouldn't get shot up on the freeways -- card games, lotteries, and dice games normally don't kill you.

That's the kind of lesson -- that the real-life consequences (financially, legally, reputationally, etc.) of guessing wrong is often devastating -- that traders and investors should take to heart as well.

Belated Post-Mortems on Amaranth

2006-10-08T08:01:00.000+01:00

Not to beat a dead horse, but here are some interesting post-mortems on Amaranth (a hedge fund that recently 'blew up') that I ran across recently. (Note: I had little to say on the matter up to this point because: (a) I was too busy to post anything to the blog while all that was happening, and (b) as I've said before, I don't like to chase after some transient news event.)

There were a couple of stories by Heather Timmons -- one for the New York Times and the other for the International Herald Tribune -- that did a good job of disecting the whole affair. The Times article focused on the foibles of one of Amaranth's young traders who made a bad bet on natural gas prices that people ascribe as the proximate cause of the blow up.

On Nassim Nicholas Taleb's non-blog section of his website titled "Notebook," he makes some interesting comments about the Amaranth situation (including brief comments on the Zelig-like coincidence of having once been in the same office complex with them in Connecticut).

Nickels, Steamrollers, & Hedge Funds

2006-10-07T04:01:00.000+01:00

I just got through reading a couple of extremely interesting articles -- one from The Economist and the other from The New York Times -- on hedge funds.

The Economist article (from the Buttonwood column), Instant Returns: Why investors have become addicted to the carry trade (Oct. 5, 2006), dissects a strategy -- the carry trade -- that is widely deployed, in one form or another, by hedge funds. (The article focuses on one variant involving foreign exchange, but the following analysis can be applied to other variants.)

Basically, the carry trade is a bet that volatility will be low. As the article aptly points out, it is the functional equivalent of writing (or selling) an option. Ceteris paribus, option writers benefit from low volatility while option holders (buyers) benefit from high volatility. The benefit from the carry trade is that traders can make a small but relatively steady stream of gains (analogous to the premium from selling options). Usually, these small series of positive returns add up to a sizable amount of profit for the hedge fund.

So what's the catch? (And there is always a catch.) This steady stream of returns come at the cost of exposing traders to the risk that there will be a punctuated jump of prices against their positions (i.e., catastrophic risk). So traders are gaining a steady paycheck at the expense that one day they might be completely ruined. As Buttonwood points out, the carry trade is like "picking up nickels in front of steamrollers."

Fortunately (or unfortunately, depending on your frame of mind) for hedge funds, investors in hedge funds create incentives for hedge fund traders/managers to use this type of strategy. For marketing, logistical, and financial reasons (and, I suppose, psychological reasons as well), hedge funds have an incentive "to produce nice, smooth returns that can be plugged into the models" of pension funds, funds of hedge funds, endowments, and investment advisors to wealthy individuals.

Unfortunately for hedge funds, according to the New York Times article, Weak Results Dim Hedge Funds’ Luster (Oct. 5, 2006), strategies, like the carry trade, employed by hedge funds are losing their edge in a complex and adaptive financial marketplace. Nonetheless, as the Times article points out, there doesn't seem to be a let up in the amount of investment (especially institutional) money chasing after hedge fund opportunities. This is despite the fact that the trend appears to be for as many hedge funds to be liquidated (or 'blow up' as has recently happened to Amaranth Advisors) as they are started. The S&P 500, up 8.5% as of September vs. hedge funds' collective 7.23%, seems to have been the better bet (especially after factoring in the high costs associated with investing in hedge funds).

The response to all of this by hedge fund supporters would be that their investment returns are somehow uncorrelated with more traditional asset classes (like vanilla investments in stocks and bonds). Even if that was true (which I doubt as a general matter), return correlations change over time (they are non-stationary in mathematical statistics-speak). So I find these claims, which attempt to overplay the notion of diversification, to be as dubious as the justifications for the carry trade.

The Undercover Economist in the Dragons' Den

2006-09-17T08:01:00.000+01:00

In his regular column for the Financial Times (UK), Tim Hartford -- the author of The Undercover Economist -- discusses a BBC reality show, Dragons' Den, that combines American Idol with venture capital investing. The article, The Undercover Economist: Shot down in flames (Sep. 15, 2006), analyzes the show -- particularly the dynamics between the hopeful entrepreneurs and the venture capitalist judges -- by applying auction theory (and related topics like the 'winner's curse') from economics and game theory. I found the observations about the information revelation that takes place in auctions -- which Dragons' Den essentially is -- to be particularly interesting:

The den is, in fact, an auction room by another name. Dragons bid against each other, and against the unknown outside offers that the business may receive, and they should be aware that every bid reveals information to the other dragons and the entrepreneur. This is the point of an auction: the seller gives buyers an incentive to reveal, through their bids, what they know about the prize’s value. The auction also, rather neatly, collects money on that basis.

I don't know if you can watch the show in the US (either on BBC America or PBS). Considering the fact that many American reality shows had there start in the UK or in Continental Europe (including American Idol), I wouldn't be shocked if some version of this show was adapted for the US.

New Yorker on Neuroeconomics

2006-09-14T22:51:00.000+01:00

The New Yorker has an article in its latest issue on neuroeconomics, Mind Games (Sep. 11, 2006). I just heard an interview on NPR with the author of the piece, John Cassidy, and it sounded interesting.

Efficient Market Hypothesis as Law

2006-09-12T22:13:00.000+01:00

The Economist has a fascinating article, Dismal science, dismal sentence (Sep. 7,2006), on how the efficient market hypothesis -- a guiding principle for many financial economists -- has been applied in the US legal system via the Supreme Court decision in Basic Inc. v. Levinson. In that decision, the Supreme Court: (1) enshrined the efficient market hypothesis (at least in its weak version) as the framework within which federal judges and juries should view the workings of the financial markets; and (2) where the actions of defendants are found to deviate from the efficient market hypothesis in securities law and securities regulation cases (such as in insider trading cases), the defendant will be deemed to have committed a 'fraud on the market' by distorting the informational value of securities prices.

There seems to be two intellectual objections to the 'fraud on the market' principle adopted by the the US federal courts and the securities regulators (e.g., the Securities and Exchange Commission). The first type of objection is that, assuming the efficient market hypothesis should be used as the guiding framework to analyze the workings of the financial markets, the courts are misapplying it by not distinguishing between the issue of relying on the distorted pricing information and the issue of what type of damages or other punishments should be associated with the distorting behavior. This argument is laid out in Bradford Cornell's paper, Market Efficiency, Crashes and Securities Litigation.

The second type of objection is that the markets aren't really that efficient any way; i.e., the efficient market hypothesis (even in a relatively weak form) shouldn't be used as the analytical framework by the courts. I should note that, even if this second type of objection should be the better economics (although not if you're from a Chicago School mindset), it is not necessarily good law since it seems to me that insiders that misuse insider information to illegallly profit should be found guilty and/or liable for committing a fraud on both the markets as well as the existing shareholders.

To paraphrase James Buchanan, a Nobel prize winning economist, law and economics don't always mix.

Math Against Terrorism

2006-09-04T23:14:00.000+01:00

A week from now, we will be commemorating the fifth anniversary of 9/11. I can still remember that morning. As I was groggily waking up in my apartment in Cambridge, Massachusetts, I was shocked to hear on my alarm clock radio that the World Trade Center had been hit by two airliners. (It shook me up even more because I had seriously thought about flying to California around that time ... so it was possible that I might have found myself on one of those planes from Boston's Logan Airport to the West Coast.) So, I think it's appropriate to write this brief blog posting on how math is being used to help in the fight against terrorism.

The best news article I've read on how mathematics is being employed in the war on terrorism is Wired News: Can Math Help in Terror War?. The article mentions the two ways that mathematicians (and I will include computer scientists, economists, mathematical psychologists, et al., in that label for the purposes of this blog post) take in applying mathematics to counter-terrorism.

The first path mathematicians take in analyzing terrorism is game theory and/or similar but alternative approaches that stem from applications in the social sciences (economics, psychology, etc.). One 'similar but alternative' approach is reflexive theory (a topic I have wroted about previously). The basic theme common to this branch of thinking is the application of mathematics to the strategic thinking of terrorists.

The second road taken by applied mathematicians in the War on Terrorism is based more on the organizational structure of terrorism (obviously, there is some overlap between strategy and organization). The methodologies approached to getting a clearer picture of the organizational structure of terrorists groups, like Al Qaeda, include Social Network Analysis and Formal Concept Analysis. These and other approaches basically boils down to drawing a 'map' of of the structure of terrorist group and/or its cells based on available data.

The assumption that underlies the attempts to uncover the organizational structure of terrorist groups is that terrorist groups are organized as, what mathematicians call, a partially ordered set (or a poset) as opposed to a totally ordered set (without getting into the technical details, think trees and/or lattices when thinking of partially ordered sets (or posets), and think of a straight line when thinking of totally ordered sets). The advantages of trying to map the partially ordered structure of terrorists groups is that: (a) it is more realistic to think there are overlapping ('horizontal') links between terrorists interspersed within any top-down ('vertical') hierarchy, and (b) this realism would, hopefully, help us to pinpoint terrorists (and/or their cells) and what importance they have within the overall organizational structure.

There are problems with taking either of the two paths -- analyzing terrorist strategy or their organization -- to battling terrorism via math. [Some of these problems are highlighted in a New York Times op-ed piece by mathematician, Jonathan Farley, The N.S.A.'s Math Problem (May 16, 2006).]

One of the problems with looking at terrorist strategy is that terrorists adapt their strategies as conditions change. For example, when it became more difficult to bring in knives and box cutters on airplanes, Al Qaeda came up with the strategy to bring hard-to-detect liquid explosives onto aircraft. Another problem with trying to unravel terrorist strategy is that strategy almost always (except for highly idealized games like chess) involves a random (or stochastic) component. In trying to unmask the strategy of terrorists, think poker instead of chess.

Trying to uncover the structure of terrorist organizations also has limitations. For example, using the methods that are currently available to us, one person who might be mis-identified (due to all of the empirical 'links' between this person and known terrorists) as a 'terrorist' would be Secretary of State Condeleeza Rice!

To be fair, the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon has succeeded in identifying the changing leadership of Hamas in the past. So, better data and better methods would probably lead to a more robust method of mapping terrorist networks, and hopefully, preventing another tragedy that woke all of us up to the dangers of terrorism on that fateful morning five years ago.

Revenge of the Long Tail

2006-09-01T00:02:00.000+01:00

There is a new Hollywood drama that is gaining a lot of attention lately starring Tom Cruise, but it's not a movie ... but if it was a movie, it might be called the 'Revenge of the Long Tail.' Sumner Redstone, the chairman of Viacom, all but ran Tom Cruise -- one of the biggest stars in Hollywood -- out of Paramount Studio's lot. A recent New York Times article, A Big Star May Not a Profitable Movie Make (Aug. 28, 2006), argues that -- from both an economics and statistical perspective -- Sumner might have been, in the article's words, "crazy like a fox."

According to the research cited in the article, there seems to be little or no significant correlation between Hollywood stars and the success of the films they star in. For example, Art Devany -- an economist who has specialized in analyzing Hollywood -- conducted research (with W. David Walls) that showed "only seven actors and actresses — Tom Hanks, Michelle Pfeiffer, Sandra Bullock, Jodie Foster, Jim Carrey, Barbra Streisand and Robin Williams — had a positive impact on the box office, mostly in the first few weeks of a film’s release. ... No other star had any statistically significant impact at all." (One could argue that ascribing success to those seven actors may be confusing correlation with causation.)

What this incident between Mr. Cruise and Mr. Redstone may represent is the realization by the business side of the entertainment industry that the huge salaries and perks demanded by the stars aren't quantitatively justified. This possible reversal of fortunes for Hollywood's star system may represent what I would have called (in a previous blog) overcoming the Tyranny of the Power Law -- where a 'Long Tail' based strategy is embraced over a more elitist strategy.

Footballmetrics

2006-08-30T23:23:00.000+01:00

In less than a week, another season of professional (American) football will begin. Football fans (me included) -- especially devotees of 'fantasy football' -- are no doubt pouring over the statistics of their favorite players. Ironically, from a statistical standpoint, this devotion to numbers may be misleading.

For example, writing in the 'Keeping Score' column in the New York Times Sports section(Numbers Often Lie When It Comes to Football, Aug. 27, 2006), economist Martin B. Schmidt argues that individual stats are so interlinked with factors beyond the inherent athletic prowess of the individual player (e.g., the individual stats are also a function of team effort, good or bad coaching, the quality of the opponents, etc.) that they are highly misleading. A good example of this is the high variance in a quaterback's passer ratings from season to season:

How much of a quarterback’s rating is predictable? Not much. If we look at six seasons of quarterbacks who threw at least 224 passes in successive seasons — the minimum to be ranked in the N.F.L.’s quarterback rating — a past rating has a poor predictive value.

Take Peyton Manning. He produced a quarterback rating of 104.1 last season. This season, based on the six seasons of ratings, there is a 95 percent chance that his rating will be between 73 and 111. In other words, he is going to be either pretty bad or pretty good.

Some innovative thinkers have tried to come up with alternatives to the currently popular statistics used by football fans, sports broadcasters, and the teams themselves. Football Outsiders is a website devoted to applying Moneyball style statistical analysis and thinking to football (Aaron Schatz, the founder of Football Outsiders, also writes a book of football statistics and analysis called Pro Football Prospectus 2006: Statistics, Analysis, and Insight for the Information Age.)

My opinion on this is that, at the very least, improved football (and sports) statistics must incorporate team effects as opposed to crediting (or blaming) the individual for too much of the success (or lack of success).

BTW, although I avoid making predictions about the stock market or the economy on this blog, I will make a prediction about a far more important issue ... football. My guess is that the Miami Dolphins will do relatively well this season (at least a playoff appearance). I should note that I am NOT a Miami Dolphin fan nor have I any ties to that region. Why am I making this bold prediction? Nick Saban, the coach of the Dolphins, is a disciple of Bill Belichick, the highly successful coach of the New England Patriots (Belichick, an economics major in college, is a supporter of applying quantitative thinking in football), and Saban will be into his second year at Miami. The Dolphins also have a new quarterback, Daunter Culpepper, who brings a lot to the table in terms of his skills as a passer and on-the-field leader of the offense. Add all of that to a defense that has been consistently good even during the lean years, and it makes for a compelling case to 'go long' (so to speak) on the Dolphins.

So if the Dolphins do well this year, you heard it here first!

PS: October 24, 2006 -- I don't know if dolphins eat crow, but I am over picking them to have success this season!!! ;)

Grigori Perelman - The Tolstoy of Math?

2006-08-27T20:24:00.000+01:00

I thought some more about the Grigori "Grisha" Perelman situation since writing about it in a previous blog post: Waiting for Grisha: What REALLY Happened to The Man Who Proved the Poincare Conjecture (Aug. 24, 2006). As a reminder, Dr. Perelman seems to have succeeded in proving the Poincare Conjecture as well as the more general Thurston Geometrization Conjecture (both conjectures are from topology and relate to the idea that geometric structures can be deformed into some basic 'shapes' identified by mathematicians).

His refusal to accept the Fields Medal has been attributed -- unfortunately in my opinion -- to some sort of eccentricity on the part of Dr. Perelman. As I wrote in the blog post, I feel that (and this is backed up by some evidence from Sylvia Nasar and David Gruber's New Yorker article, Manifold Destiny) the more plausible reason behind Dr. Perelman's declining the honor had to do more with his desire to uphold his high moral, ethical, and intellectual standards rather than to the less than flattering reasons offered up by most of the press and by (again, unfortunately) some mathematicians. As Dr. Perelman himself so eloquently put it (in the New Yorker article): “'It is not people who break ethical standards who are regarded as aliens,' he said. 'It is people like me who are isolated.'”

All of this reminded me of another Russian who possessed both a great intellect and a great sense of moral integrity: Leo Tolstoy. Like Dr. Perelman, Tolstoy -- after giving the world some of the best novels ever written (War and Peace, Anna Karenina) -- retired to an ascetic/quasi-monastic life motivated by a deep sense of personal morality and ethical integrity.

So it is my sincere hope that Grisha Perelman will not be seen as some sort of 'nutty professor' -- has he has been unfairly portrayed by many in the press and by some mathematicians -- but will, instead, be seen as the 'Tolstoy of math.'

Macroeconomic Derivatives

2006-08-27T08:01:00.000+01:00

Another interesting article from the NBER Digest: Macroeconomic Derivatives. Justin Wolfers, of Wharton, and another economist studied the effectiveness of markets to purchase binary/digital options (so-called because you either get the payoff if the event happens or you don't if the event doesn't occur) in predicting macroeconomic events. Their findings were that forecasts based on these markets were at least as good as (and often superior to) surveys of forecasters/economists. A particularly interesting aspect of the research was that it might be possible to construct a probability distribution -- what they call a "density forecasts" -- using the market-based data. Creating actual probability distribution from economic/financial data is very hard to do for a number of reasons, so it is remarkable that one can use these binary options to create such "density forecasts."

A copy of the paper can be found here.