Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

被引:12
|
作者
Wang, Shan [1 ]
Jiang, Zhi-Qiang [1 ,2 ]
Li, Sai-Ping [2 ,3 ]
Zhou, Wei-Xing [1 ,2 ,4 ]
机构
[1] E China Univ Sci & Technol, Sch Business, Dept Finance, Shanghai 200237, Peoples R China
[2] E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China
[3] Acad Sinica, Inst Phys, Taipei 11529, Taiwan
[4] E China Univ Sci & Technol, Sch Sci, Dept Math, Shanghai 200237, Peoples R China
基金
中国国家自然科学基金;
关键词
Econophysics; Technical analysis; Data-snooping; Bootstrap method; Superior predictive ability; REALITY CHECK; PROFITABILITY;
D O I
10.1016/j.physa.2015.07.029
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient. (C) 2015 Elsevier B.V. All rights reserved.
引用
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页码:114 / 123
页数:10
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