时变风险厌恶与人民币汇率波动率--基于GARCH-MIDAS-SK模型的实证研究  

Time-Varying Risk Aversion and RMB Exchange Rate Volatility:An Empirical Study Based on GARCH-MIDAS-SK Model

作　　者：吴鑫育[1] 梅学婷 周海林[1] 尹学宝 WU Xin-yu;MEI Xue-ting;ZHOU Hai-lin;YIN Xue-bao(School of Finance,Anhui University of Finance and Economics,Bengbu 233030,China)

机构地区：[1]安徽财经大学金融学院,安徽蚌埠233030

出　　处：《数理统计与管理》2024年第4期721-736,共16页Journal of Applied Statistics and Management

基　　金：国家自然科学基金项目(71971001);安徽省高校自然科学研究重点项目(KJ2019A0659);安徽财经大学研究生科研创新基金项目(ACYC2020185);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)拔尖人才学术资助项目(gxbjZD2022019)。

摘　　要：经验研究表明汇率收益率分布呈现出时变高阶矩(偏度和峰度)特征,其对于汇率波动率建模和预测具有重要作用。同时众多研究表明,时变风险厌恶(RA)包含了金融波动率预测的相关信息。鉴于此,本文构建带时变高阶矩的GARCH-MIDAS-SK模型框架,进一步将RA指数引入该模型框架,实证检验RA对人民币汇率波动率的影响以及预测作用。实证结果表明:RA对人民币汇率波动率具有显著负的影响;人民币汇率收益率分布展现出明显的时变高阶矩特征;引入RA和时变高阶矩有助于提高模型的样本内拟合效果。基于损失函数和MCS检验证实了引入RA和时变高阶矩能够显著提高模型的样本外预测精度,且预测结果具有关于不同样本外预测阶段的稳健性。Empirical studies demonstrate that exchange rate return distributions exhibit properties of time-varying higher moments(skewness and kurtosis),which plays an important role in modeling and forecasting exchange rate volatility.Moreover,numerous studies show that time-varying risk aversion(RA)contains useful information for forecasting financial volatility.In light of this,this paper proposes the GARCH-MIDAS-SK framework that incorporates time-varying higher moments and RA to empirically investigate the impact and predictive role of RA on RMB exchange rate volatility.The empirical results show that RA has a significant negative impact on RMB exchange rate volatility.The RMB exchange rate return distributions exhibit obviously properties of time-varying higher moments.Incorporating RA and time-varying moments improves the in-sample fitting of the model.Furthermore,the loss functions and MCS test confirm that incorporating RA and time-varying higher moments leads to significantly more accurate out-of-sample volatility forecasts.The finding is robust to different out-of-sample forecasting periods.

关 键 词：时变风险厌恶 时变高阶矩 人民币汇率波动率 GARCH-MIDAS-SK模型 MCS检验 

分 类 号：O212[理学—概率论与数理统计]