Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost

IR > 计算机与通信学院

	Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost
	Wang, Yan; Guo, Yuankai
	2020-03
发表期刊	CHINA COMMUNICATIONS
ISSN	1673-5447
卷号	17 期号:3 页码:205-221
摘要	Stock price forecasting is an important issue and interesting topic in financial markets. Because reasonable and accurate forecasts have the potential to generate high economic benefits, many researchers have been involved in the study of stock price forecasts. In this paper, the DWT-ARIMA-GSXGB hybrid model is proposed. Firstly. the discrete wavelet transfonn is used to split the data set into approximation and error parts. Then the ARIMA (0, 1, 1), ARIMA (1. 1, 0), ARIMA (2, 1. 1) and ARIMA (3, 1. 0) models respectively process approximate partial data and the improved xgboost model (GSXGB) handles error partial data. Finally, the prediction results are combined using wavelet reconstruction. According to the experimental comparison of 10 stock data sets, it is found that the errors of DWT-ARIMA-GSXGB model are less than the four prediction models of ARIMA, XGBoost, GSXGB and DWT-ARIMA-XGBoost. The simulation results show that the DWT-ARIMA-GSXGB stock price prediction model has good approximation ability and generalization ability, and can fit the stock index opening price well. And the proposed model is considered to greatly improve the predictive performance of a single ARIMA model or a single XGBoost model in predicting stock prices.
关键词	hybrid model discrete wavelet transform ARIMA XGBoost grid search stock price forecast
收录类别	SCI ; SCIE
语种	英语
WOS研究方向	Telecommunications
WOS类目	Telecommunications
WOS记录号	WOS:000522830300018
出版者	CHINA INST COMMUNICATIONS
来源库	WOS
引用统计	被引频次：45[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/76640
专题	计算机与通信学院
通讯作者	Guo, Yuankai
作者单位	LanZhou Univ Technol, Coll Comp & Commun, Lanzhou 730050, Peoples R China
第一作者单位	计算机与通信学院
通讯作者单位	计算机与通信学院
第一作者的第一单位	计算机与通信学院
推荐引用方式 GB/T 7714	Wang, Yan,Guo, Yuankai. Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost[J]. CHINA COMMUNICATIONS,2020,17(3):205-221.
APA	Wang, Yan,&Guo, Yuankai.(2020).Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost.CHINA COMMUNICATIONS,17(3),205-221.
MLA	Wang, Yan,et al."Forecasting Method of Stock Market Volatility in Time Series Data Based on Mixed Model of ARIMA and XGBoost".CHINA COMMUNICATIONS 17.3(2020):205-221.