Profiting from a contrarian application of technical trading rules in the US stock market

Abstract

Using the variance ratio test, we cannot reject the random walk null hypothesis for three major U.S. stock market indexes between 1990 and 2005. Consistent with this result, we find that the naïve forecasting model based on the random walk assumption generates more accurate forecasts as compared to the ARIMA forecasting model. We find that the regular application of three commonly used technical trading rules (the moving average crossover rule, the channel breakout rule, and the Bollinger band breakout rule) under-perform the buy-and-hold strategy between 1990 and 2005. However, we observe significant positive returns on trades generated by the contrarian version of these three technical trading rules, even after considering a 0.5% transaction costs on all trades. Moreover, we find that while the contrarian version of these rules results in a significantly higher probability of success as compared to the regular version, it results in a significantly lower payoff ratio than that generated by the regular version.