The Information Content of Charts: Algorithm and Evidence from Hong Kong Stock Market
This study Introduces an improved method for nonparamctric regression and pattern identification in the research of technical analysis based on the concept of stopping time. We are interested in the efficacy, predictability, and profitability of 10 patterns from chart analysis. Using Hong Kong stock data, we attempt to identify these patterns and test their predictability and profitability. We find that most of them demonstrate predictability with regard to future price trend. Some of them even show profitability against the null hypothesis of randoM walk. Furthermore, we find some connections between price and trading volume behavior in one or two patterns.
Technical analysis Nonparametric Regression Pattern Identification
Hongbing Ouyang
School of Economics Huazhong University of Science and Technology Wuhan, China School of Information Science and Technology Sun Yat-Sen University Guangzhou, China
国际会议
北京
英文
268-272
2009-11-21（万方平台首次上网日期，不代表论文的发表时间）