Financial Data Prediction by means of Evolutionary Computation(Forecasting Technology and its Reliability)

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  • IBA Hitoshi
    東京大学大学院新領域創成科学研究科基盤情報学専攻

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  • 進化論的手法を用いた金融データの予測(予測技術の信頼性)
  • 進化論的手法を用いた金融データの予測
  • シンカロンテキ シュホウ オ モチイタ キンユウ データ ノ ヨソク

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Abstract

There have been several applications of Evolutionary Computation (EC) to the financial problems, such as portfolio optimization, bankruptcy prediction, financial forecasting, fraud detection and scheduling. This paper presents the application of Genetic Programming (GP) to the prediction of the price data in Japanese stock market. The goal of this task is to choose the best stocks when making an investment and to decide when and how many stocks to sell or buy. We describe how successfully GP and its variant, i.e., STROGANOFF, are employed to predicting the stock data so as to gain the high profit. The comparative experiments are conducted with neural networks to show the effectiveness of the GP-based approach.

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