| Title: | Using Genetic Programming with Lambda Abstraction to Find Technical Trading Rule |
| Authors: | 陳樹衡;T.Yu;T.-W. Kuo |
| Date: | 2004-07 |
| Issue Date: | 2009-01-09 11:21:15 (UTC+8) |
| Abstract: | 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 |
| Relation: | No 200, Computing in Economics and Finance 2004 from Society for Computational Economics |
| Data Type: | conference |
| Appears in Collections: | [Department of Economics] Proceedings
|
