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Stock Market Prices Do Not Follow Random Walks : Evidence from a Simple Specification Test

How would deleveraging affect a bank’s weighted average cost of funds? Our results suggest that if leverage declines, the cost of equity will also fall. For example, if leverage of the average bank halves to 10, the market beta would fall by 10 basis points. This implies that the average equity factor for banks will fall by 0.4% to 13.0%. Assuming a 5% cost of debt, the weighted average cost of funds for the bank would be 5.8% (ie 0.10*13.0% + 0.90*5%). 7 This is only about 40 basis points higher than when leverage is equal to 20, the average. | . 2 Stock Market Prices Do Not Follow Random Walks Evidence from a Simple Specification Test Since Keynes 1936 NOW FAMOUS PRONOUNCEMENT that most investors decisions can only be taken as a result of animal spirits of a spontaneous urge to action rather than inaction and not as the outcome of a weighted average of benefits multiplied by quantitative probabilities a great deal of research has been devoted to examining the efficiency of stock market price formation. In Fama s 1970 survey the vast majority of those studies were unable to reject the efficient markets hypothesis for common stocks. Although several seemingly anomalous departures from market efficiency have been well documented 1 many financial economists would agree with Jensen s 1978a belief that there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Markets Hypothesis. Although a precise formulation of an empirically refutable efficient markets hypothesis must obviously be model-specific historically the majority of such tests have focused on the forecastability of common stock returns. Within this paradigm which has been broadly categorized as the random walk theory of stock prices few studies have been able to reject the random walk model statistically. However several recent papers have uncovered empirical evidence which suggests that stock returns contain predictable components. For example Keim and Stambaugh 1986 find statistically significant predictability in stock prices by using forecasts based on certain predetermined variables. In addition Fama and French 1988 show that See for example the studies inJensen s 1978b volume on anomalous evidence regard-ing market efficiency. 17 18 2. Stock Market Prices Do Not Follow Random Walks long holding-period returns are significantly negatively serially correlated implying that 25 to 40 percent of the variation of longer-horizon returns is predictable from past returns. In this chapter we .