使用基因程式規劃預測股票買賣時機

Using Genetic Programming to Predict Timing for Buy or Sell Stocks

吳榮訓(Roung-Shiunn Wu) ； 廖高賢(Kuo-Shuang Liao)

《資訊管理學報》 14卷2期 (2007/04) Pp. 111-138

https://doi.org/10.6382/JIM.200704.0111

摘要

預測股票走勢的方法有基本分析及技術分析兩類，技術分析是頗受歡迎的一種分析方式，主要是技術分析在判讀上並不一定需要有受過財經教育的專業能力，一般投資人均可以使用技術分析來預測股價走勢。本研究主要目的是使用技術分析中的價量關係為預測變數，並使用十分鐘為一筆記錄的交易資料，應用基因程式規劃的快速搜尋及最佳化能力，透過歷史資料的學習，建立一個股票市場的股價預測模式，利用所建立的模式掌握個別股的未來動態與趨勢，使投資人能從中獲利。由於股票市場交易結構會隨著時問不斷改變，在訓練過程採用移動視窗的方式，以產生更符合市場動態的交易規則，然後和買進持有策略進行比較，期望在獲利上能優於買進持有策略。此外也將做基因程式規劃參數的實驗，以找出適合本研究的最佳參數。模擬實證的結果顯示，在考慮交易成本下，使用價量關係預測方式能打敗買進持有策略獲得超額的報酬，且依十分鐘交易資料進行預測，當買賣訊號出現時，即可在盤中立刻買進或賣出，操作比使用日資料預測還靈活。實驗中亦發現提高複製率及交配率時可以達到較佳的演化效果，產生較佳的交易規則。

關鍵字

技術分析 ； 基因程式規劃 ； 價量關係 ； 機器學習

並列摘要

In term of stock market analysis, two schools are developed to analyze stock price by using either fundamental analysis or technical analysis. The major goal of fundamental analysis is to pick the right stocks to invest on. While technical analysis can be applied to provide price-and-volume relationship or indexes information for decision making when to trade stocks. To make profit from stock market, one must have capability to pick the right stocks and to know when to buy or sell them. In this research we applied genetic programming along with a machine learning methodology as technical analysis tool and used price-and-volume relationship as predicting parameter. By taking advantage of searching and optimizing capacities of genetic programming, a prediction model was developed using archive price and volume data for training individual stock. The prediction model generated trading rules. These rules were applied to detect timing for trading.

並列關鍵字

Technical Analysis ； Genetic Programming ； Price-and-Volume Relationship ； Machine Learning

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