遺傳演算法建構台灣股市期貨買賣決策規則之研究

Building Taiwan Stock Futures Market Trading Rule Using Genetic Algorithms

連立川(Li-Chuan Lien) ； 葉怡成(I-Cheng Yeh) ； 江宗原(Chiang-Thuang Yuan) ； 楊豐銘(Feng-Ming Yang)

《資管評論》 14期 (2006/03) Pp. 47-61

https://doi.org/10.6131/MISRb.200603_(14).0003

摘要

本研究採用台灣大盤股價指數及成交值所轉換的18種價量技術指標做為輸入參數，以期末資金最大化做為適應度函數，應用遺傳演算法（Genetic Algorithms）的最佳化能力建構台灣大盤加權指數的買賣決策規則。研究結果顯示，本研究所比較之三種交易策略：雙向GA買賣決策策略、單一雙向GA買賣決策策略及買入持有策略，在測試範例期間的平均年獲利率分別是10.72%、6.30%與-7.2%以及平均相對獲利係數分別是1.19、1.15與1.00。另外由雙向GA買賣決策策略及單一雙向GA買賣決策策略的風險評估得知，其最小年獲利率分別為2.96%與-16.90%及最小總成功率分別為46.70%與26.40%。因此，在雙向獲利的條件下所產生的雙向GA買賣決策規則是一個穩定且有效的台灣股市交易策略。

關鍵字

技術指標 ； 遺傳演算法 ； 買賣決策規則

並列摘要

This research used 18 kinds of price and volume technical indices transferred from the Taiwan stock price index as the input parameters, the maximization of the final capital as the fitness function, the genetic algorithms as the optimization tool to construct the trading rules for the Taiwan stock price index. The findings showed that the three kinds of trading strategies, the bidirectional GA strategy, the sole bidirectional GA strategy, and the buy and hold strategy, in test period produced the average year profit rate respectively with 10.72%, 6.30% and -7.2%, as well as the relative profit coefficient respectively with 1.19, 1.15 and 1.00. Moreover, compared the risk assessment of the bidirectional GA strategy and the sole bidirectional GA strategy, the smallest year profit rate respectively is 2.96% and -16.90%, and the smallest total success ratio respectively is 46.70% and 26.40%. Therefore, the bidirectional GA strategy is a not only effective but also stable Taiwan stock market trading strategy.

並列關鍵字

technical index ； genetic algorithms ； trading rule

參考文獻

Allen, F.,Karjalainen, R.(1999).Using Genetic Algorithms to Find Technical Trading Rules.Journal of Finance Economics.51,245-271.

Armano, Giuliano(2002).Stock market prediction by a mixture of genetic-neural experts.International Journal of Pattern Recognition and Artificial Intelligence.16,501-526.

Davis, L.(1991).Handbook of Genetic Algorithms.Van No strand Reinhold, NY.

Goldberg, D. E.(1989).Genetic Algorithms in Search, Optimization and Machine Learning.Addison-Wesley Publishing Company.

Holland, J. H.(1975).Adaptation in Natural and Artificial System.Ann Arbor:University of Michigan Press.