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

Hui Qu () and Xindan Li

Computational Economics, 2014, vol. 43, issue 3, 311 pages

Abstract: 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. Copyright Springer Science+Business Media New York 2014

Keywords: Technical trading system; Genetic programming; Treelike structured; Market efficiency (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10614-013-9369-8

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