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https://ah.lib.nccu.edu.tw/handle/140.119/23009
題名: | Using Genetic Programming with Lambda Abstraction to Find Technical Trading Rule | 作者: | 陳樹衡;T.Yu;T.-W. Kuo | 日期: | Jul-2004 | 上傳時間: | 9-Jan-2009 | 摘要: | Using GP with lambda abstraction module mechanism to generate technical trading rules based on S&P 500 index, we find strong evidence of excess returns over buy-and-hold after transaction cost on the testing period from 1989 to 2002. The rules can be interpreted easily; each uses a combination of one to four widely used technical indicators to make trading decisions. The consensus among GP rules is high, with most of the time 80% of the evolved rules give the same decision. The GP rules give high transaction frequency. Regardless of market climate, they are able to identify opportunities to make profitable trades and out-perform buy-and-hold | 關聯: | No 200, Computing in Economics and Finance 2004 from Society for Computational Economics | 資料類型: | conference |
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