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Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks

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  • Segnon, Mawuli
  • Gupta, Rangan
  • Wilfling, Bernd

Abstract

We investigate the role of geopolitical risks in forecasting stock market volatility at monthly horizons within a robust autoregressive Markov-switching GARCH mixed-data-sampling (AR-MSGARCH-MIDAS) framework. Our approach accounts for structural breaks through regime switching and allows us to disentangle short- and long-run volatility components. We conduct an empirical out-of-sample forecasting analysis using (i) daily Dow Jones Industrial Average returns, and (ii) monthly sampled geopolitical risks and macroeconomic variables over a time span of 122 years. We find that the impact of geopolitical risks as explanatory variables for stock market volatility forecasts at monthly horizons hinges crucially on the specific prediction model chosen by the forecaster. After capturing the non-stationarities in the data via an MSGARCH framework, we do not find significant forecast accuracy improvements through the inclusion of geopolitical risk indices.

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  • Segnon, Mawuli & Gupta, Rangan & Wilfling, Bernd, 2024. "Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks," International Journal of Forecasting, Elsevier, vol. 40(1), pages 29-43.
    • Handle: RePEc:eee:intfor:v:40:y:2024:i:1:p:29-43
    DOI: 10.1016/j.ijforecast.2022.11.007
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    Cited by:

    1. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    2. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    3. Afees A. Salisu & Ahamuefula E.Oghonna & Rangan Gupta & Oguzhan Cepni, 2024. "Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach," Working Papers 202409, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    Geopolitical risks; Volatility forecasts; Markov-switching GARCH-MIDAS; EPA tests; Model confidence sets;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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