Skewness Preference Analysis Of Stock Technical Strategies

Technical analysis, as expressed in the decision making of trading assets, is a study of collective market sentiment, techniques that can be used on a broad range of financial instruments such as equities, bonds, currency futures, and commodity futures. Technical analysis tends to use the past information, commonly price and volume data, to forecast the future movement of assets' prices. Over the past decades, more and more funds managers or investment banks tends to use technical analysis to exploit potension profitability opportunity.Albeit technical analysis is proved to be increasingly popular, academics tends to be skeptical about the validity of technical analysis based on the belief that the market is efficient, at least in its weak form. If the market is efficient, even in its weak form, technical analysis would be invalid and unprofitable given that current price has already incorporated all the past information. Many exsiting empirical literature has intensively researched the profitability of technical analysis. However, there is still no collectively consent about the validity of technical analysis. For example, Allen and Karjalainen(1999) found that after adjusting for transaction cost, the profit of technical analysis was even lower than the profit of random walk model. However, for instance, Lukac et al(1998) investigated the profitabilility of technical analysis on 12 futures market, they found 1.90%-2.78% significant monthly return.Given that there is no clear evidence to show that technical analysis is profitable or valid for investors, why more and more investors tend to use technical analysis to make investment decision? This paper offers a new explanation for the preference of technical analysis based on behavioral finance theory. This paper chooses four most popular technical strategies in the industry, and investigate the performance of these four technical strategies on all the stocks listed on New York Stock Exchange. I find that, at least for the four technical strategies I selected, all the technical strategies strongly skew the trading return distribution to the right, exhibiting strong positive skewness. Strong positive skewness of technical strategies return distribution means that investors would incur a small loss with large probability and obtain a extreme gain with small probability, a characterics which is consistent with the preference of cumulative prospect theory investors.Comparing with the existing literature which try to explain the polularity of techincal strategies based on the inefficiency of market and the profitability of technical strategies, the results of this paper does not depend on the profitability of technical strategies, or even independent with the profitability of technical strategies. In this paper, I show that irrespect to the profitability, the right skewed return distribution of technical strategies is strongly consistent with the preference of cumulative prospect theory investors. Therefore, this paper offer a new explanation to the popularity of technical strategies from a new angle.