Efficient Market Hypothesis
SECURITY ANALYSIS AND PORTFOLIO MANAGEMENT | EFFICIENT MARKET HYPOTHESIS | |
MRIGANKA DAS, 13/09 |
INTRODUCTION:
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,
MRIGANKA DAS, 13/09 |
INTRODUCTION:
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,