A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predi...A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.展开更多
基金Yaojie Zhang acknowledges the financial support from the National Natural Science Foundation of China(72001110)the Fundamental Research Funds for the Central Universities(30919013232)+4 种基金the Research Fund for Young Teachers of School of Economics and Management,NJUST(JGQN2009)Yudong Wang acknowledges the financial support from the National Natural Science Foundation of China(72071114)Feng Ma acknowledges the support from the National Natural Science Foundation of China(71701170,72071162)Yu Wei acknowledges the support from the National Natural Science Foundation of China(71671145,71971191)Science and technology innovation team of Yunnan provincial.
文摘A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility.To address this issue,we find a phenomenon,“momentum of jumps”(MoJ),that the predictive ability of the jump component is persistent when forecasting the oil futures market volatility.Specifically,we propose a strategy that allows the predictive model to switch between a benchmark model without jumps and an alternative model with a jump component according to their recent past forecasting performance.The volatility data are based on the intraday prices of West Texas Intermediate.Our results indicate that this simple strategy significantly outperforms the individual models and a series of competing strategies such as forecast combinations and shrinkage methods.A mean–variance investor who targets a constant Sharpe ratio can realize the highest economic gains using the MoJ-based volatility forecasts.Our findings survive a wide variety of robustness tests,including different jump measures,alternative volatility measures,various financial markets,and extensive model specifications.
