Efficient Market Hypothesis and Behavioral Finance – Is a Compromise in Sight?

Topics: Stock market, Fundamental analysis, Financial markets Pages: 20 (6438 words) Published: December 3, 2010
Efficient Market Hypothesis And Behavioral Finance – Is A Compromise In Sight? By Nikolai Chuvakhin

Legend has it that once upon the time two economists were walking together when one of them saw something that struck his mind. “Look,” he exclaimed, “here’s a great research topic!” “Nonsense,” the other one said, “If it were, someone would have written a paper on it by now.” For a long time this attitude governed the view of economists toward the stock market. Economists simply believed that the stock market was not a proper subject for serious study. Indeed, most of the pre-1960 research on security prices was actually done by statisticians. The Pre-History: Statistical Research Most of the early statistical research of the stock market concentrated around the same question: are security prices serially correlated? Do security prices follow a random walk? Are prices on any given day as likely to go up as they are to go down? A number of studies concluded that successive daily changes in stock prices are mostly independent. There seemed to be no pattern that could predict the future direction of price movements. One of the most interesting (and currently relevant) research projects of that earlier era was undertaken by Harry Roberts, a statistician at the University of Chicago. In his paper, “Stock Market ‘Patterns’ and Financial Analysis,” published in the Journal of Finance in 1959, Roberts wrote: If the stock market behaved like a mechanically imperfect roulette wheel, people would notice the imperfections and, by acting on them, remove them. This rationale is appealing, if for no other reason than its value as counterweight to the popular view of stock market “irrationality,” but it is obviously incomplete. Roberts generated a series of random numbers and plotted the results to see whether any patterns that were known to technical analysts would be visible. Figure 1 provides an example of Roberts’ plot:

Efficient Market Hypothesis And Behavioral Finance—Is A Compromise In Sight?

Figure 1. Simulated stock price path

Those somewhat acquainted with technical patterns might recognize a familiar head and shoulders formation, which technical analysts believe to be one of the surest indicators of a trend reversal. At this point, the reader may take pause. Are these stock price patterns of value or not? If they work even on decidedly random series, isn’t there a contradiction? Maybe not. Consider a hypothetical example of a stock price path in Figure 2. If tomorrow the price of this stock goes down, there will be a clearly visible head and shoulders pattern, which should signal a trend reversal. If, however, the price goes up, the resulting formation will look more like a pennant pattern, which, according to market technicians, signals the renewal of the trend. In other words, technical patterns are easy to see only when it is too late to act on them.



Figure 2. Hypothetical example of technical patterns formation


Today, anyone can replicate Roberts’ results using a common spreadsheet program. In his popular textbook, Financial Modeling, Simon Benninga of the Wharton Business School devotes an entire chapter to simulating stock price paths using Microsoft Excel.


Efficient Market Hypothesis And Behavioral Finance—Is A Compromise In Sight?

Returning to Harry Roberts, his paper turned out to be almost prophetic in one major respect. He wrote: Perhaps the traditional academic suspicion about the stock market as an object of scholarly research will be overcome. As we shall see during the rest of this presentation, Roberts was right. The Pre-History: CRSP Another enabling factor for the soon-to-follow boom in stock market research was provided by an initially small outfit based at the University of Chicago, the Center for Research in Securities Prices (CRSP). CRSP was established by James H. Lorie in 1960 and provided comprehensive data on all stocks traded on the New York Stock...
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