Fama (1965) stated that successive values of a stock are independent of each other and random in nature. This random event which is caused by the changes in stock information is known as the random walk hypothesis. To provide a more detail explanation, Fama (1965) mentioned that a random walk evolves from the basis of the stock market being an efficient market, which explains that a stock market consists of many unreasonable investors competing with one another to make profits by trying to predict the future value of the stocks and all significant information is freely available to every market participants. It can be said that the stock prices reflect all relevant information available. Fama further explained …show more content…
In other words, common movements in expected returns do exist and can be predicted. The study conducted by Keim and Sambaugh covered the period beginning from 1927 until 1978 in examining the predictability of risk premiums in terms of the sensitivity of each of the variables to the asset prices and the seasonality of the risk premium. The results of the study depict that the stocks of small market capitalization companies and low grade bonds are more sensitive to asset prices in the month of January as compared to other months of the year, thereby showing the seasonal patterns. Therefore, it is likely to predict that both stocks and bonds tend to have significantly higher returns in the first month of the year.
An evidence has been discovered that proves the stock prices do not trail the random walk theory in the test of autocorrelations of stock returns for longer holding periods as mentioned by Fama and French (1988). It is revealed that the long holding period returns have significant negative autocorrelations in its sample period starting from 1926 until 1985. It is also inferred that 25 to 40 percent of the variation of a longer term returns is able to be forecasted based on past returns. This findings support the deduction that the elements of mean reverting stock prices are essential to the returns