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Predicting Stock Index Time Series Based on Nonlinear Dynamics and Asymmetrical Support Vector Regression

Abstract

作为经济生活中一个很重要的部分,股票市场是一个复杂的非线性动力系统,因此预测股市是非常困难的。但是由于股市预测的经济意义重大,它在金融投资领域占有及其重要的地位,一直以来都是人们关注的焦点。 随着股票市场混沌现象的发现和证明,许多预测混沌时间序列的技术被用来预测股票价格,并取得了一定的成果。本文选取了香港恒生指数和美国道琼斯指数时间序列来作为研究对象。首先,在对数据平稳化处理后,本文利用C-C法同时选取了相空间重构的两个关键参数:延迟时间和嵌入维数,从而完成了对股指序列的相空间重构。然后,利用G-P法计算了关联维数、利用小数据量法计算了最大Lyapunov指数来作为重构质量的评估,结果证明对...As an essential part in the economic life, the stock market is a complicated nonlinear dynamic system which decides the difficulties in predicting stock price. However, due to the great economic influences, predicting stock price is always an important issue in financial investment and is always a focus of people's attention. In the end of last century, many economists discovered and proved ...学位:工学硕士院系专业:信息科学与技术学院自动化系_系统工程学号:20043106

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