Using Genetic Programming to Find Technical Trading Rules for SSE 50 Index
To avoid data snooping bias induced by the common approach of testing market efficiency through popular technical trading rules,genetic programming is proposed to find optimal technical trading rules.The first generation of technical trading rules is randomly generated tree structures of basic functions,optimized by genetic programming.Data are divided into training period and testing period using moving windows.The technical trading rules get optimized generation by generation using the training data,while the subsequent testing data are used to test the optimization result′s out-of-sample performance.Using daily price and volume data for the SSE 50 index from January 2,2004 to March 12,2010,we find out that genetic programming generated best technical trading rules have statistically significant out-of-sample excess return compared with buy-and-hold considering realistic transaction cost.Therefore,we conclude that Chinese stock market has not achieved weak-form efficiency.