Random walk hypothesis
The concept can be traced to French broker Jules Regnault who published a book in 1863, and then to French mathematician Louis Bachelier whose Ph.D. dissertation titled "The Theory of Speculation" (1900) included some remarkable insights and commentary.
The same ideas were later developed by MIT Sloan School of Management professor Paul Cootner in his 1964 book The Random Character of Stock Market Prices.
[1] The term was popularized by the 1973 book A Random Walk Down Wall Street by Burton Malkiel, a professor of economics at Princeton University,[2] and was used earlier in Eugene Fama's 1965 article "Random Walks In Stock Market Prices",[3] which was a less technical version of his Ph.D. thesis.
[4] In 1993 in the Journal of Econometrics, K. Victor Chow and Karen C. Denning published a statistical tool (known as the Chow–Denning test) for checking whether a market follows the random walk hypothesis.
[5] Whether financial data can be considered a random walk is a venerable and challenging question.
To investigate whether observed data follows a random walk, some methods or approaches have been proposed, for example, the variance ratio (VR) tests,[6] the Hurst exponent[7] and surrogate data testing.
[8] Burton G. Malkiel, an economics professor at Princeton University and author of A Random Walk Down Wall Street, performed a test where his students were given a hypothetical stock that was initially worth fifty dollars.
Thus, each time, the price had a fifty-fifty chance of closing higher or lower than the previous day.
Malkiel then took the results in 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'.
Malkiel argued that this indicates that the market and stocks could be just as random as flipping a coin.
Modelling asset prices with a random walk takes the form:
[10] Martin Weber, a leading researcher in behavioural finance, has performed many tests and studies on finding trends in the stock market.
Professors Andrew W. Lo and Archie Craig MacKinlay, professors of Finance at the MIT Sloan School of Management and the University of Pennsylvania, respectively, have also presented evidence that they believe shows the random walk hypothesis to be wrong.
Their book A Non-Random Walk Down Wall Street, presents a number of tests and studies that reportedly support the view that there are trends in the stock market and that the stock market is somewhat predictable.
[12] Lo and MacKinlay have authored a paper, the adaptive market hypothesis, which puts forth another way of looking at the predictability of price changes.
[13] Peter Lynch, a mutual fund manager at Fidelity Investments, has argued that the random walk hypothesis is contradictory to the efficient market hypothesis -- though both concepts are widely taught in business schools without seeming awareness of a contradiction.
