Makings of a Chinese Stockmarket Bubble?

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

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)

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

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

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

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

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."