基于SVM的金融时间序列分析的研究
Financial time series analysis based on SVM
本文通过比较支持向量机（SVM）和自回归移动平均模型(ARIMA)在金融时间序列回归分析的实验，提出了一种新的SVM和ARIMA的组合模型。该模型结合了支持向量机泛化能力好，拟合精度高的优点，也汲取了ARIMA模型考虑历史数据和未来数据相关性的优势。它可以更好的适应金融时间序列分析领域的回归分析。 以上海证券综合指数为实验数据，本文通过实验验证了组合模型的有效性。
his paper provides a comparison between the SVM and ARIMA models in financial time series analysis, and gives a new model which is the combination of SVM and ARIMA models. The combined model has both the good points of SVM and ARIMA, and it is more appropriate for analysis in financial time series analysis. Through an experiment on Shanghai Complex Index series, this paper proves the new model’s feasibility and efficiency in financial time series analysis.
刘迪
财政、金融数学计算技术、计算机技术
金融时间序列分析支持向量机回归自回归移动平均模型
financial time series analysisSupport Vector Machine RegressionRIMA
刘迪.基于SVM的金融时间序列分析的研究[EB/OL].(2009-05-05)[2025-08-14].http://www.paper.edu.cn/releasepaper/content/200905-88.点此复制
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