Research on Exchange Rate Volatility Based on Multi-factor Mixed Frequency Time Series Model
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.
CNY exchange rateVolatilityMixing time series modelMulti-factor
NETL
NSTL
万方数据
