基于Boosting算法的期货市场预测

Yun-peng Wu, Jia-min Mao, Weifeng Li
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引用次数: 8

摘要

AdaBoost是一种基于促进想法的机器学习算法。AdaBoost是adaptive boosting的缩写,是一种将弱分类器组装为强分类器的算法。金融市场存在大量的数据噪音。为了识别期货市场的潜在趋势,我们建议使用标准化的技术指标来预测涨跌,并创新地采用AdaBoost算法对这些指标进行组合。采用AdaBoost算法对各技术指标的权重进行优化,得到了较好的预测结果。本研究表明,这些弱分类器可以有效地过滤期货市场中的数据噪声,表明机器学习可以在传统金融工程分析方法的基础上获得更好的分析结果。本研究对个人投资者具有一定的指导意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predication of Futures Market by Using Boosting Algorithm
AdaBoost is a machine learning algorithm based on boosting ideas. AdaBoost is the abbreviation of adaptive boosting, which is an algorithm for weak classifier to assemble as a strong classifier algorithm. There is a lot of data noise in finance market. In order to identify underlying trends in futures market, we propose to use standardized technical indicators to forecast rise or fall and assemble these indicators by AdaBoost algorithm innovatively. We use AdaBoost algorithm to optimize the weight of technical indicators and a good predication result is received. This research shows that these weak classifier can filter data noise in futures market effectively and exhibits that machine learning can get a better analysis result based on the conventional finance engineering analysis methods. This research is meaningful for individual investors.
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