Trend Prediction of FDI Based on the Intervention Model and ARIMA-GARCH-M Model

被引：2

作者：

Shi, Hongyan ^{[1
]}

Zhang, Xin ^{[2
]}

Su, Xiaoming ^{[1
]}

Chen, Zhongju ^{[3
]}

机构：

[1] Shenyang Univ Technol, Sch Sci, Shenyang Shenliao Rd 111, Shenyang 110000, Peoples R China

[2] Shenyang Univ Technol, Grad Sch, Shenyang 110000, Peoples R China

[3] Liaoning Adm Coll Pol & Just, Shenyang 110000, Peoples R China

来源：

CONFERENCE ON MODELING, IDENTIFICATION AND CONTROL | 2012年 / 3卷

关键词：

ARIMA model; GARCH-M model; avelet de-noising; autocorrelation; prediction;

D O I：

10.1016/j.aasri.2012.11.061

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

For providing the government with effective monitoring of the trends of the economic variables in the future and good reference for developing a reasonable policy, in this paper, we establish a time series model on China's Foreign Direct Investment (FM) by using wavelet analysis and intervention analysis and time series analysis and predict the trend of FDI in the next several years. This model eliminates the interference of noise for predicting by using wavelet analysis, and describes the autocorrelation and time-varying volatility of the financial time series by using ARIMA- GARCH-M model. The simulation results show that this model explains the dynamic structure of China's FDI trends well. (C) 2012 The Authors. Published by Elsevier Ltd. Selection and/or peer review under responsibility of American Applied Science Research Institute

引用

页码：387 / 393

页数：7

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