Efficient Market Hypothesis

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The Efficient Market Hypothesis and Random Walks
One of the early applications of computers in economics in the 1950s was to analyze economic time series. Business cycle theorists believed tracing the evolution of several economic variables over time would clarify and predict the progress of the economy through boom and bust periods. A natural candidate for analysis was the behavior of the stock market prices over time. Assuming stock prices reflect the prospects of the firm, recurring patters of peaks and troughs in economic performance ought to show up in those prices. In 1953 Maurice Kendall, a British statistician, presented a controversial paper to the Royal Statistical Society on the behavior of stock and commodity prices.1 Kendall had expected to find regular price cycles, but to his surprise they did not seem to exist. Each series appeared to be “a ‘wandering’ one, almost as if once a week the Demon of Chance drew a random number… and added it to the current price to determine the next week’s price.” In other words, the prices of stocks and commodities seemed to follow a random walk. When Maurice Kendall suggested that stock prices follow a random walk, he was implying that the price changes are independent of one another just as the gains and losses in the coin-tossing games are independent. The figure below illustrates this. Each dot shows the change in the price of Microsoft stock on successive days. The circled dot in the southeast quadrant refers to a pair of days in which a 1 percent increase was followed by a 1 percent decrease. If there was a systematic tendency for increased to be followed by decreases, there would be many dots in the southeast quadrant and few in the northeast quadrant. It is obvious from a glance that there is very little pattern in these price movements. In fact, the coefficient of correlation between each days’ price change and the next is only +0.022, i.e., there is only a negligible tendency for price rises to be followed by further price rises. More generally, one could say that any publicly available information that might be used to predict stock performance, including information on the macro economy, the firm’s industry, and its operations, plans, and management, should already be reflected in stock prices. As soon as there is any information indicating a stock is underpriced and offers a profit opportunity, investors flock to buy the stock and immediately bid up its price to a fair level, where again only ordinary rates of return can be expected. These “ordinary rates” are simply rates of return commensurate with the risk of the stock. But if prices are bid immediately to fair levels, given all available information, it must be that prices increase or decrease only in response to new information. New information, by definition, must be unpredictable; if it could be predicted, then that prediction would be part of today’s information. Thus, stock prices that change in response to new information must move unpredictably. Randomness in price changes should not be confused with irrationality in the level of prices. If prices are determined rationally, then only new information will cause them to change. Therefore, a random walk would be the natural consequence of prices that always reflect all current knowledge. Indeed, if stock price movements were predictable, that would be damning evidence of stock market inefficiency, because the ability to predict prices would indicate that all available information was not already impounded in stock prices. The first use of the term “efficient market” appeared in a 1965 paper by Eugene Fama4, who defined it as:

“a market where there are large numbers of rational, profit-maximizes actively competing, with each trying to predict future market...
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