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Building Technical Trading System with Genetic Programming: A New Method to Test the Efficiency of Chinese Stock Markets

机译:用遗传程序建立技术交易系统:一种测试中国股市效率的新方法

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摘要

Testing whether technical trading rules can beat buy-and-hold strategy is a common approach to study the efficiency of stock markets. Noticing that the common approach of evaluating popular technical trading rules' profitability would result in the biases of data snooping and incomplete test, we build a technical trading system with genetic programming to test the efficiency of Chinese stock markets. This system takes historical prices and volumes as inputs, randomly generates treelike structured technical trading rules composed of basic functions, and optimizes the rules using genetic programming according to the inputs. Using daily prices and volumes of Shenzhen Stock Exchange 100 index from January 2, 2004 to March 12, 2010, we find out that the optimal technical trading rules generated by our technical trading system have statistically significant out-of-sample excess returns compared with buy-and-hold strategy considering realistic transaction costs. Therefore, we conclude that Chinese stock markets have not achieved weak-form efficiency.
机译:测试技术交易规则是否能击败并购策略是研究股票市场效率的常用方法。注意到评估流行的技术交易规则的获利能力的通用方法会导致数据监听和不完整测试的偏差,因此我们建立了一个具有遗传程序设计的技术交易系统来测试中国股票市场的效率。该系统以历史价格和交易量为输入,随机生成由基本功能组成的树状结构的技术交易规则,并根据输入的遗传规划来优化规则。使用2004年1月2日至2010年3月12日的深交所100指数的每日价格和交易量,我们发现,与买入相比,我们的技术交易系统生成的最佳技术交易规则具有统计上显着的样本外超额收益。考虑实际交易成本的保留策略。因此,我们得出的结论是,中国股市尚未达到弱形式的效率。

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