Random Walk Hypothesis

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The random walk hypothesis is a financial theory stating that stock market prices evolve according to a random walk and thus the prices of the stock market cannot be predicted. Investors, economists, and other financial behaviorists have historically given into the random walk hypothesis. They have run several tests and still believe that stock prices are completely random because of the efficiency of the market.

[edit] Testing the Hypothesis

Burton G. Malkiel, an economist professor at Princeton University and writer of A Random Walk Down Wall Street, did a test where his students were given a hypothetical stock that was initially worth fifty dollars. The closing stock price for each day was determined by a coin flip. If the result was heads the price would close a half point higher, and subsequently if the result was tails, it would close a half point lower. Each time there was a fifty-fifty chance of the price closing higher or lower than the previous day. There were cycles or trends determined from the tests. Malkiel then took the results in a chart and graph form to a chartist (a person who “seeks to predict future movements by seeking to interpret past patterns on the assumption that ‘history tends to repeat itself’”) (Keane 11). The chartist told Malkiel that they needed to immediately buy the stock. When Malkiel told him it was based purely on flipping a coin, the chartist was very unhappy. This indicates that the market and stocks could be just as random as flipping a coin.

The random walk hypothesis was also applied to NBA basketball. Psychologists did a detailed study of every shot the Philadelphia 76ers made over one and one-half seasons of basketball. The psychologists found no positive correlation between the previous shots and the outcomes of the shots afterwards. Economists and believers in the random walk hypothesis apply this to the stock market. The actual lack of correlation of past and present can be easily seen. If a stock goes up one day, no stock market participant can accurately predict that it will rise again the next. Just as a basketball player with the “hot hand” can miss his or her next shot, the stock that seems to be on the rise can fall at any time, making it completely random.

[edit] A Non-Random Walk Hypothesis

There are other economists, professors, and investors that believe that the market is predictable to some degree. The people believe that there are trends and incremental changes in the prices and when looking at them, one can determine whether the stock is on the rise or fall. There have been key studies done by economists and even a book written by two professors of economics that try to prove the random walk hypothesis wrong.

Martin Weber, a leading researcher in behavioral finance, has done many tests and studies on finding trends in the stock market. In one of his key studies, he observed the stock market for ten years. Over those ten years, he looked at the market prices and looked for any kind of trends. He found that stocks with high price increases in the first five years tended to become under-performers in the following five years. Weber and other believers in the non-random walk hypothesis cite this as a key contributor and contradictor to the random walk hypothesis.

Another test that Weber ran that contradicts the random walk hypothesis was finding stocks that have had an upward revision for earnings outperform other stocks in the forthcoming six months. With this knowledge, investors can have an edge in predicting what stocks to pull out of the market and what stocks, the stocks with the upward revision, to leave in. Martin Weber’s studies detract from the random walk hypothesis, because according to Weber there are trends and other tips to predicting the stock market. Professors Andrew W. Lo and Al. Craig MacKinlay professors of Finance at Sloan School of Management and the University of Pennsylvania, respectively, have also tried to prove theory wrong. They wrote the book A Non-Random Walk Down Wall Street, that goes through a number of tests and studies that try to prove that there are trends in the stock market and they are some what predictable. They try to prove it with what is called the simple volatility-based specification test which is an equation that states:

Xt = μ + Xt-1 + £t

The term Xt = the price of the stock.

μ = arbitrary drift parameter (randomly changing factor.)

Xt-1 = price of the stock minus 1.

£t = random disturbance term (Random term the disrupts the stock)

With this equation they have been able to put in stock prices over the last number of years, and figure out the trends that have unfolded (Non-Random 19). They have found small incremental changes in the stocks throughout the years. Through these changes Lo and MacKinlay believe that the stock market is predictable, thus contradicting the random walk hypothesis.

[edit] References

• Fromlet, Hubert. "Behavioral Finance-Theory and Practical Application." Business Economics July 2001: 63.
• Keane, Simon M. Stock Market Efficiency. Oxford: Philip Allan Limited, 1983.
• Lo, Andrew W., and A. C. Mackinlay. A Non-Random Walk Down Wall Street. 5th ed. Princeton: Princeton University P, 2002. 4-47.
• Malkiel, Burton G. A Random Walk Down Wall Street. 6th ed. New York: W.W. Norton & Company, Inc., 1973.