Price Predictions Based on Evolvable Strategies, Principal Component Analysis, and Randomness of Data Strings

Mieko Tanaka, Xin Yang, Ryota Itoi
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Abstract

– This paper summarizes the trials of predicting price movements in the financial market in various ways. The first example is to use the framework of the game theory between two players by regarding the next price movement as the next action of a player and the information of the environ-ment surrounding the price movement as the action of the opponent player by using the evolutional computation. The second example is to predict trendy sectors by using RMT-PCA. The third example is to use the randomness of the price fluctuations by means of the RMT-test. An empirical rule “High randomness predicts a good performance in the next period” is extracted by studying the randomness of stocks in the period of 2007-2009.
基于可进化策略、主成分分析和数据串随机性的价格预测
本文总结了各种方法预测金融市场价格走势的试验。第一个例子是使用两个玩家之间的博弈论框架,通过使用进化计算将下一个价格运动视为玩家的下一个动作,并将围绕价格运动的环境信息视为对手玩家的动作。第二个例子是使用RMT-PCA预测热门行业。第三个例子是通过rmt检验来利用价格波动的随机性。通过对2007-2009年股票随机性的研究,得出了“高随机性预示着下一时期的良好表现”的经验规律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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