文献详情
Technical Analysis Profitability Without Data Snooping Bias: Evidence from Chinese Stock Market
文献类型：期刊
通讯作者：Tong, GS (reprint author), Renmin Univ China, Hanging Adv Inst Econ & Finance, Beijing 100872, Peoples R China.
期刊名称：INTERNATIONAL REVIEW OF FINANCE
年：2019
卷：19
期：1
页码：191-206
ISSN：1369-412X
所属部门：汉青高级经济与金融研究院
摘要：We perform a comprehensive analysis on the profitability of a large number of technical analysis based trading rules in Chinese stock market. To counter data snooping bias, we employ a stepwise superior predictive ability test to identify genuinely profitable trading rules among more than 28,000 technical signals. Using 19 years of daily data on Chinese aggregate stock market return, we find substantial evidence on the profitability of technical trading rules measured by either the market timing ...More
We perform a comprehensive analysis on the profitability of a large number of technical analysis based trading rules in Chinese stock market. To counter data snooping bias, we employ a stepwise superior predictive ability test to identify genuinely profitable trading rules among more than 28,000 technical signals. Using 19 years of daily data on Chinese aggregate stock market return, we find substantial evidence on the profitability of technical trading rules measured by either the market timing ability or Sharpe ratio gain. Our results on the profitability of technical rules hold during different subperiods and remain valid under the presence of transaction costs. ...Hide

DOI：10.1111/irfi.12161
百度学术：Technical Analysis Profitability Without Data Snooping Bias: Evidence from Chinese Stock Market
语言：外文
被引频次：1
基金：National Natural Science Foundation of ChinaNational Natural Science Foundation of China [71602198, 71572052]; Beijing Natural Science FoundationBeijing Natural Science Foundation [9174045]; Program for Innovation Research in Central University of Finance and Economics
作者其他论文



Market Timing under Limited Information: An Empirical Investigation in US Treasury Market.Tong, Guoshi,.ANNALS OF ECONOMICS AND FINANCE. 2017, 18(2), 291-322.