计算机仿真2024,Vol.41Issue(7) :383-389.

基于多因子混频GARCH的汇率波动性研究

Research on Exchange Rate Volatility Based on Multi-factor Mixed Frequency Time Series Model

赵耀 张英辉
计算机仿真2024,Vol.41Issue(7) :383-389.

基于多因子混频GARCH的汇率波动性研究

Research on Exchange Rate Volatility Based on Multi-factor Mixed Frequency Time Series Model

赵耀 1张英辉1
扫码查看

作者信息

  • 1. 西安财经大学行知学院,陕西 西安 710026
  • 折叠

摘要

宏观经济环境的变化会传导作用于外汇市场,然而宏观数据多为月度低频数据,汇率为日度高频数据,这使得自变量与因变量之间的时间间隔不一.鉴于此,选用GARCH-MIDAS与GJR-GARCH两种混频时间序列模型对其展开研究,选择Shibor,M2 与工业增加值的水平值作为宏观低频输入变量,通过滑动窗口测得的 22 日CNY/USD汇率方差作为真实波动率的代理变量.结果表明:低频成分的解释变量会对高频汇率的条件方差产生影响,利率以及利率与其它因子的双因子组合具有相对较好的拟合性,且这些因子对长期成分非对称性影响是不显著的.

Abstract

Changes in the macroeconomic environment can have in impact on the foreign exchange market.How-ever,the macro data are mostly monthly low-frequency data,and the exchange rate is daily high-frequency data,which makes the time interval between the independent variable and the dependent variable different.In view of this,this paper selects GARCH-MIDAS and GJR-GARCH two mixed frequency time series models to study it,selects Shi-bor,M2 and the level of industrial added value as comprehensive input variables,and measures the 22-day CNY through a sliding window.The variance of the USD exchange rate as a proxy for true volatility.The results show that the explanatory variables of the low-frequency components will have an impact on the conditional variance of the high-frequency exchange rate,the interest rate and the two-factor combination of interest rates and other factors have a relatively good fit,and these factors have no significant effect on long-term compositional asymmetry.

关键词

人民币汇率/波动性/混频时间序列模型/多因子

Key words

CNY exchange rate/Volatility/Mixing time series model/Multi-factor

引用本文复制引用

基金项目

陕西省教育厅专项科学研究计划(19JK0330)

出版年

2024
计算机仿真
中国航天科工集团公司第十七研究所

计算机仿真

CSTPCD
影响因子:0.518
ISSN:1006-9348
参考文献量3
段落导航相关论文