经济政策不确定性与人民币汇率波动率--基于CARR-MIDAS模型的实证研究  

Economic Policy Uncertainty and Renminbi Exchange Rate Volatility:Evidence from CARR-MIDAS Model

作　　者：吴鑫育[1] 谢海滨[2] 马超群[3] Wu Xinyu;Xie Haibin;Ma Chaoqun(School of Finance,Anhui University of Finance and Economics,Bengbu 233030,China;School of Banking and Finance,University of International Business and Economics,Beijing 100029,China;Business School,Hunan University,Changsha 410082,China)

机构地区：[1]安徽财经大学金融学院,安徽蚌埠233030 [2]对外经济贸易大学金融学院,北京100029 [3]湖南大学工商管理学院,湖南长沙410082

出　　处：《中国管理科学》2024年第8期1-14,共14页Chinese Journal of Management Science

基　　金：国家自然科学基金项目(71971001);安徽省高校自然科学研究项目(KJ2019A0659);安徽省高校协同创新项目(GXXT-2021-078);安徽省自然科学基金项目(2208085Y21);安徽省高校杰出青年科研项目(2022AH020047);安徽省高校学科(专业)拔尖人才学术项目(gxbjZD2022019)。

摘　　要：本文在经典的基于极差的条件自回归极差(CARR)模型基础上,借鉴基于收益率的GARCH-MIDAS模型的建模思路,提出基于极差的CARR-MIDAS模型对人民币汇率波动率进行建模。该模型框架充分利用了日内极值信息,且允许低频宏观经济变量(宏观经济信息)通过波动率长期成分和灵活的MIDAS结构直接影响波动率。采用月度全球经济政策不确定性(EPU)指数和日度美元兑人民币(USD/CNY)汇率数据,利用引入EPU的基于极差的CARR-MIDAS(CARR-MIDAS-EPU)模型,实证检验了EPU对USD/CNY汇率波动率的影响及预测作用。实证结果表明:EPU对USD/CNY汇率长期波动率具有显著正向影响,即EPU水平的提高会加剧USD/CNY汇率长期波动率;基于极差的CARR-MIDAS-EPU模型相比其他众多竞争模型(包括基于收益率的GARCH模型、GARCH-MIDAS模型和GARCH-MIDAS-EPU模型以及基于极差的CARR模型和CARRMIDAS模型)在不同的预测期上(从1天到3个月)具有显著更高的样本外波动率预测精确性,说明极差和EPU包含了USD/CNY汇率波动率预测的重要信息。采用不同版本的全球EPU指数和不同的样本外预测窗口进行稳健性分析,进一步证实了上述研究结论的可靠性。Financial volatility modeling and forecasting has always been a hot topic in financial econometrics,due to its great importance for derivative pricing,asset allocation and risk management.Typically,GARCH model is used to describe the dynamics of financial volatility.However,the GARCH model uses squared return to measure volatility,ignoring the information of intraday price movements.An alternative approach for measuring volatility is to employ the intraday range,which is calculated using the intraday high and low prices.Apparently,the intraday range makes full use of the intraday price information(extreme value information),which is a more efficient volatility estimator than the squared return volatility estimator.A classical model for describing the dynamics of the intraday range is the conditional autoregressive range(CARR)model,which produces more accurate volatility forecasts than the return-based GARCH model.Despite the empirical success of the range-based CARR model,it cannot capture the impact of macroeconomic variables(macroeconomic information)on financial volatility.In recent years,the level of economic policy uncertainty(EPU)keeps rising,due to a series of events including the US-China trade war and the coronavirus(COVID-19)pandemic.Intuitively,high EPU may affect investors'investment decisions and hence financial market.The foreign exchange market is one of the largest and most liquid financial markets in the world,which is of great relevance for investors and policy-makers and would have a close relation to EPU.As the currency of the world's second largest economy,renminbi plays a more and more important role in the world economy.Since the implementation of renminbi exchange rate regime reform in 2005,the renminbi exchange rate has experienced significant fluctuations.Accurate prediction of the renminbi exchange rate volatility has become increasingly important.To our knowledge,there are few studies investigating the impact of EPU on the renminbi exchange rate volatility.Inspired by the return-based

关 键 词：极差 人民币汇率波动率 经济政策不确定性 GARCH-MIDAS CARR-MIDAS 

分 类 号：F830.9[经济管理—金融学]