Technical Analysis and Stock Returns

Abstract

This paper investigates the profitability of technical analysis in Korea stock markets. In this paper, I construct some characteristic portfolios sorted on six proxies which plausibly represent the underlying risk variation source of expected return, information uncertainness. I implement technical trading rules on these underlying characteristic portfolios, and compare the technical rule strategy return series to buy-and-hold benchmark return series. I find that the technical strategies generate substantially excess returns over the buy-and-hold strategy both in statistic and economic sense. The abnormal risk adjusted returns (alpha) are significant and the traditional asset pricing models fail to absorb this anomaly. The pattern is that for highly information uncertain portfolios, the technical rules generate higher abnormal returns. It is an intuition that, for the behavioral point of view, the more uncertain the information for a firm, the more behavioral biases the investors will perform. Thus technical analysis matters much on the uncertain stocks, since most of technical rules are trends following and momentum detecting. I select firm’s size, return volatility, turnover rate, firm listing age, foreigner holding ratio, institution recommendation number, six variables for sorting proxies. Value-weighted portfolios and long-short hedging portfolios are formed for each set of characteristic portfolios. The results show that the excess returns are consistent with the degree of information uncertainty and cannot be explained by the traditional asset pricing models. To address the abnormal returns, trend factor are constructed by the PCA. The trend factor performs well than conventional momentum factor in R-squared sense. In conclusion, this paper finds that over 10-year sample period technical analysis does provide incremental information to make significant positive excess return and the profitability positively relates to the degree of uncertainty.