2021
DOI: 10.1002/for.2837
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Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models

Abstract: This study adds ample evidences on forecasting oil futures realized range‐based volatility (RRV) in the mixed data sampling (MIDAS) framework. Considering the features and frequent extreme risk in oil futures trading in practice, we investigate the effect of jumps, leverage effect, and regime switching. The results highlight the great importance of combing jumps, leverage effect, and regime switching simultaneously in oil futures RRV forecasting, which still holds the best predictability during a highly volati… Show more

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Cited by 3 publications
(2 citation statements)
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“…As a result of unexpected shocks, market volatility would increase rapidly and stock prices would fall wildly for a short time ( Eraker et al, 2003 ). The so-called dramatic discontinuous variations are likely to be jumps ( Caporin et al, 2017 ; Wang et al, 2020a , Wang et al, 2020c ; Lu et al, 2021 ; Roh et al, 2021 ). The essential difference between price jumps and huge price volatility is the unpredictability of the jumping behavior, which indicate a severe impact on investors' psychological expectations ( Lu et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…As a result of unexpected shocks, market volatility would increase rapidly and stock prices would fall wildly for a short time ( Eraker et al, 2003 ). The so-called dramatic discontinuous variations are likely to be jumps ( Caporin et al, 2017 ; Wang et al, 2020a , Wang et al, 2020c ; Lu et al, 2021 ; Roh et al, 2021 ). The essential difference between price jumps and huge price volatility is the unpredictability of the jumping behavior, which indicate a severe impact on investors' psychological expectations ( Lu et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…There is a heterogeneity in investors' investment horizons due to the differences in beliefs and utility functions (Kim & In, 2010;Lu et al, 2022;Rehman et al, 2022), factors that have received extensive attention in risk spillover (Dai et al, 2020(Dai et al, , 2023, hedging (Hou & Li, 2013;Sultan et al, 2019), and causality studies (Gloßner, 2019;Tong et al, 2022). However, the key challenge faced by the study of investment horizon heterogeneity in the portfolio optimization problem is the data loss issue under the classical definition of asset returns, which makes it difficult to forecast asset returns and evaluate portfolio strategies.…”
Section: Introductionmentioning
confidence: 99%