Crude oil volatility forecasting: Insights from a novel time-varying parameter GARCH-MIDAS model

Lijuan Peng, Chao Liang, Baoying Yang and Lu Wang

International Review of Economics & Finance, 2024, vol. 94, issue C

Abstract: Stationary GARCH-MIDAS models encounter challenges in effectively capturing the dynamic impact of realized volatility on crude oil price volatility. This study introduces a novel time-varying parameter GARCH-MIDAS (TVP-GARCH-MIDAS) model to address these challenges and intricately capture the evolving dynamics between variables. The empirical results underscore the superior precision of the TVP-GARCH-MIDAS model in reflecting the influence of realized volatility on crude oil price volatility over time. In comparison to the stationary GARCH-MIDAS and MS-GARCH-MIDAS models, the proposed model exhibits outstanding out-of-sample forecasting performance and has excellent economic significance. This study provides valuable insights for investors and policy-makers, supporting better risk management and more effective investment strategy formulation.

Keywords: Crude oil price; GARCH-MIDAS; Volatility forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 Q43 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:94:y:2024:i:c:s1059056024004052

DOI: 10.1016/j.iref.2024.103413

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