基于主成分分析和NARX动态神经网络的股市情绪指数构建与预测

兰州大学机构库 >数学与统计学院

	基于主成分分析和NARX动态神经网络的股市情绪指数构建与预测
Alternative Title	Construction and Prediction of Stock Market Sentiment Index Based on PCA and NARX Dynamic Neural Network
	陈雯吉
Thesis Advisor	严定琪
	2016-05-14
Degree Grantor	兰州大学
Place of Conferral	兰州
Degree Name	硕士
Keyword	情绪指数主成分分析 NARX ARIMA
Abstract	目前关于股市情绪指数的研究大多使用单一的情绪变量，而构建情绪指数的研究不多。动态神经网络应用于股市情绪指数方面的研究也较少。大多数情绪指数的构建也只停留在基本的时间序列分析上，运用的是传统的回归模型或者时间序列模型，利用动态神经网络并且以传统时间序列模型作为效果对比的研究较少。本文对目前使用的情绪指数构建进行了优化，分析了BW情绪指数构建的前提条件，根据提取共同因素的思想提出了一种新思路。如果每个代理变量都包含三个层面的信息，即共同的基本因素、共同的情绪因素和特质因素，那么先对每个代理变量进行剔除基本因素的处理后，所提取的主成分即是投资者情绪。与现有研究不同的是，本文通过多个单一情绪变量指标，利用主成分分析方法构建情绪指数，再通过NARX动态神经网络进行实证分析。最后，用传统的时间序列ARIMA模型作为对比，得出NARX动态神经网络用于回归预测上海综合股价指数是可行的，并且结果好于ARIMA模型。
Other Abstract	At present,most researches about the stock market sentiment index use the single emotion variable,but few on the emotion index.The research of dynamic neural network based on the stock market sentiment index is even less.Most sentiment index construction still stay in the basic analysis of time series,which uses traditional regression model and time series model.The research that using dynamic neural network are less than the traditional time series ones.This paper optimized current construction of the sentiment index,analyzed premise situation of constructing BW sentiment index,proposed a new idea according to the extracted common factors.If each agent variable contains three levels of information,as common basic factors,common emotional factors and characterized factors,the first extracted principal component is investor sentiment after exclusion of basic factors. This paper is different from the existing research by a plurality of single emotion variable,constructed sentiment index used principal analysis,and making empirical investigation through NARX neural network. Finally,it compared by the traditional time series ARIMA model.The conclusion is the forecasting results of the Shanghai composite index from NARX neural network is feasible,which is better than the one produced from ARIMA model.
URL	查看原文
Language	中文
Document Type	学位论文
Identifier	https://ir.lzu.edu.cn/handle/262010/225069
Collection	数学与统计学院
Recommended Citation GB/T 7714	陈雯吉. 基于主成分分析和NARX动态神经网络的股市情绪指数构建与预测[D]. 兰州. 兰州大学,2016.

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