Keynes and the casino
Few economists have been successful investors, and quite a few have been disastrous failures. But after a narrow escape from disaster early in his investing career John Maynard Keynes made a fortune for his Cambridge college by speculating in futures markets It is a striking paradox that Keynes was among the most scathing of all economists in his assessment of the role of financial markets.
During the decades of the long Keynesian boom, financial markets were tightly regulated, and, as a result, financial crises disappeared almost entirely from the experience and memory of the developed world. At the margin, substantial profits could be made by finding ways to work around the regulations, while relying on governments to maintain the stability of the system as a whole. Not surprisingly, there was a warm reception for theoretical arguments that presented a more favorable view of financial markets.
Keynes’ views were reflected in the systems of financial regulation adopted as governments sought to rebuild national economies and the global economic system in the wake of World War II. The international negotiations undertaken at a meeting in Bretton Woods, New Hampshire, in 1944, where Keynes represented the British government, established an international framework in which exchange rates were fixed and movements of capital tightly controlled.
National governments similarly adopted policies of stringent financial regulation, and established a range of publicly-owned financial institutions in response to the failures of the private market. In the United States, a host of regulatory bodies were established to control financial institutions. The Glass-Steagall Act established the Federal Deposit Insurance Corporation (FDIC) and prohibited bank holding company from owning other financial companies. The Federal National Mortgage Association (later quasi-privatised as Fannie Mae, and then renationalised during the early stages of the 2008 meltdown) was established to support the mortgage market.
Although the details of intervention varied from country to country, the effect was the same everywhere. Banking in the 1950s and 1960s was a dull but secure business, resembling a public utility in many respects. Parents scarred by the Depression urged their children to look for ‘a nice safe job in a ban’.
The Efficient Markets Hypothesis changed all that.
The rise of the EMH began relatively modestly with the argument that the prices of assets such as stocks cannot be predicted from their past movements in they way claimed by “chartists” and “technical analysts”. In the popular terminology, prices follow a ‘random walk’. This idea had been put forward as early as 1900 in a neglected paper by a French statistician, Louis Bachelier, but it was not rediscovered until the 1950s.
The simple idea behind the random walk hypothesis was that, since everyone in the market could see the history of prices, any predictable pattern would soon be exploited and the very process of trying to exploit it would eliminate the pattern. The random walk hypothesis went against the powerful human tendency to find patterns in data, whether they exist or not. But it stood up well to initial statistical testing, and has done so ever since.
None of the patterns typically analysed by students of stock market charts, such as trends, reversals and support levels, appear to be of any use in predicting stock price movements. There remains some dispute about whether subtler features of the behavior of stock prices are consistent with the possibility of a profitable trading strategy based solely on observation of past prices.
A handful of anomalies such as the ‘weekend effect’ (prices tending to fall on Fridays and rise on Mondays) have been observed. However, the effects are usually too small to permit traders to gain significant profits after trading costs are taken into account. And most disappeared not long after they were discovered.
Two explanations of the disappearance of anomalies, both consistent with EMH might be considered. First, it may be that once the anomaly was publicised traders sought to exploit it (for example by selling on Thursday and buying at the Friday close). But such a pattern would produce a price increase on Fridays, and a decline on Mondays, wiping out the anomaly it sought to exploit.
The second, simpler, explanation is that the anomalies were just the product of human pattern-finding. The famous curse of the zero years provides an illustration. Beginning with the election of William Harrison in 1840, who died of pneumonia in 1841, all Presidents elected in zero years, up to and incluidng JFK died in office. It was after the Kennedy assassination that the curse was apparently discovered. But the next potential victim, Ronald Reagan, elected in 1980, survived for two terms and lived to the age of 93. George W. Bush also survived two terms, and the curse is now forgotten.
At a more sophisticated level, Andrew Lo, Director of MIT's Laboratory for Financial Engineering has argued that because of investor irrationality, asset prices display some momentum over time. But this claim remains controversial, as does the performance of algorithmic trading strategies designed to exploit such patterns.
Among economists, the random walk hypothesis, now referred to as the ‘weak form’ of the EMH, is fairly generally accepted, and even the sceptics agree that any violations of weak-form EMH are subtle and hard to exploit. In a striking instance of the inefficiency of financial markets, however, investment banks continue to employ “technical analysts” using charting methods, decades after such methods have been shown not to work. The human desire to believe that there must be a way to beat the odds is reflected in the prevalence on the Internet of “systems” guaranteed to make you a winner betting on the horses or at the roulette table.
The ‘strong’ EMH
The argument underlying the random walk hypothesis was that the existence of predictable price patterns in efficient markets with rational and well-informed traders was logically self-contradictory. Empirical tests showed that a random walk model fitted the data very well, suggesting that real markets were indeed efficient, at least in this limited sense.
It wasn’t long before economic theorists realised that the same argument applied to other kinds of information, such as information about the likely future earnings of companies. If this information is publicly available, then traders should take it into account, just as they do with the past history of the stock price. So, the stock price will be the best available estimate of the future value of the stock, taking account of all available information.
The key steps in the discovery of the strong EMH were taken independently by Paul Samuelson, the leading Keynesian economic theorist of the postwar era, and Eugene Fama, who soon became a leading figure in the free-market Chicago school, and is widely regarded as the father of modern finance. As we will see, they took the idea in rather different directions.
There was one more subtle distinction to make before the EMH assumed its modern form. The arguments so far concerned publicly available information, but what about information that was only available to some people, such as company insiders, or customers? Some theorists argued that such information would inevitably be reflected in market trades. Others stuck with the traditional focus on publicly available information.
Fama proposed a distinction between the weak form (EMH), which excluded profitable trading based on price history, the semi-strong form, which extended the claim to cover publicly available information, and the strong form, which claimed that the stock price incorporates all information held by traders, whether it is public of private.
 Since the weak form of the EMH is relatively uncontroversial and mostly unimportant, I will use the term EMH to refer to the strong and semi-strong versions from now on. Where the distinction between the two is important, I will try to make it clear which one I mean.
Black-Scholes and the rise of finance-driven capitalism
Although the EMH made a big difference to the way economists viewed financial markets, initially it had much less impact on financial markets themselves. An entertaining and economically literate description of the stock market scene in the 1960s, The Money Game by ‘Adam Smith’ (a pseudonym for George Goodman) describes ‘a random walk professor choking on his icecream at the thought that there are people called “technicians” who claim to forecast the stock market”, but makes it clear that the vast majority of Wall Streeters believed the technicians more than the economists.
The economic theory that really changed thinking in financial markets was the model of pricing options developed in a 1973 paper by Fischer Black and Myron Scholes and subsequently formalised by Robert Merton. The model was named Black-Scholes, but Merton got his share of the glory when he shared the 1997 Nobel Memorial Prize in Economics with Scholes (Black had died two years earlier).
The Black Scholes model showed that, under plausible assumptions, it was possible to duplicate the payoff from an option by a combination of trades in the original stock and in high-grade bonds. Hence, the ‘right’ option price could be calculated by looking at the interest rate on bonds and the variability of the stock price. If the market price differed from the Black-Scholes price, traders could make money with little or no risk by combining trades in the two markets.
It took some time for financial traders to come to grips with the Black-Scholes model, and, while they did, sophisticated “quants” or “rocket scientists” who understood the model made big profits at the expense of old-fashioned traders working on rules of thumb and “seat of the pants” judgement. Eventually, the quants came to dominate the market and prices came more and more into line with the Black Scholes rule. The quants went on to design more and more exotic derivatives on which to practise their skills, and the role of finance theory was established, seemingly on a firm foundation of success.
There was something of a paradox here. The Black-Scholes pricing rule shows how an option price ought to be determined in an efficient market. But traders can only make a profit using Black-Scholes and similar rules to price derivatives if the market price deviates from the ‘correct’ price, that is, if the efficient markets hypothesis is not satisfied. This paradox was given a rigorous formulation in a famous 1980 article by Sanford Grossman and Joseph Stiglitz, one of the contributions that later earned Stiglitz the Nobel Prize in economics.
Economists have wrestled with the Grossman-Stiglitz paradox for a long time without working out a completely satisfactory solution. The most common view was one that seemed to preserve the efficient markets hypothesis while justifying the huge returns reaped by financial market professionals. This is the idea that the market is just close enough to perfect efficiency that the returns available from exploiting any inefficiency are equal to the cost of the skill and effort that goes into discovering it.
With this accommodation, the EMH, which now formed the basis of the dominant approaches to financial economics, could co-exist with a large and expanding financial sector devoted to finding, exploiting, and thereby eliminating, opportunities for profitable trades. For those unable to afford such expensive talent, the EMH offered a solution: simply buy a portfolio of stocks that mimics, as closely as possible, the market as a whole. Investment in such index-linked securities has grown to reach 40 or 50 per cent of total capital holdings. There is, however, a catch. With such a large share of the market allocated to index-linked funds, it is difficult to tell how closely any given index matches the holdings of the informed investors the index-linked strategy is trying to mimic.
 An option is one of the simplest kinds of financial derivatives, that is, assets derived from other assets. An option gives you the right to buy (or sell) a given stock at a given price and on a given date