罗纯, 陈雪平, 张应山. 金融时间序列的转折点分析[J]. 应用概率统计, 2010, 26(4): 437-442.
引用本文: 罗纯, 陈雪平, 张应山. 金融时间序列的转折点分析[J]. 应用概率统计, 2010, 26(4): 437-442.
Luo Chun, Chen Xueping, Zhang Yingshan. The Turning Point Analysis of Finance Time Series} \newcommand{\enkeywords}{Time series, risk fuction, relatively departure index, information-decomposition ratios of departure index.[J]. Chinese Journal of Applied Probability and Statistics, 2010, 26(4): 437-442.
Citation: Luo Chun, Chen Xueping, Zhang Yingshan. The Turning Point Analysis of Finance Time Series} \newcommand{\enkeywords}{Time series, risk fuction, relatively departure index, information-decomposition ratios of departure index.[J]. Chinese Journal of Applied Probability and Statistics, 2010, 26(4): 437-442.

金融时间序列的转折点分析

The Turning Point Analysis of Finance Time Series \newcommand\enkeywordsTime series, risk fuction, relatively departure index, information-decomposition ratios of departure index.

  • 摘要: 本文讨论了时间序列的预测问题, 在摆脱了在传统模型过多假设的基础上, 采用对不同类型预测模型进行综合平衡分析的方法, 权衡各项指标, 以达到发现时间按序列转折点的目的. 并以股票序列为例说明所给预测模型的有效性.

     

    Abstract: This paper discusses the prediction of time series. Without the assumptions on the traditional time series models, this paper considers all the indicators by balancing different types of forecasting models, so that the turning point in the time series can be found. An example of stock time series is given to show the effectiveness of the predictive model provided.

     

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