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

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

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

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

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.)

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

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.'