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Forecasting Risk with Markov-Switching GARCH Models: A large-scale performance study

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  • David Ardia, Swaziland
  • Keven Bluteau, Swaziland
  • Kris Boudt, Vrije Universiteit Brussel, Belgium and VU University Amsterdam, Netherlands
  • Leopoldo Catania

We perform a large-scale empirical study in order to compare the forecasting performances of single-regime and Markov-switching GARCH (MSGARCH) models from a risk management perspective. We find that MSGARCH models yield more accurate Value-at-Risk, expected shortfall, and left-tail distribution forecasts than their single-regime counterparts for daily, weekly, and ten-day equity log-returns. Also, our results indicate that accounting for parameter uncertainty improves the left-tail predictions, independently of the inclusion of the Markov-switching mechanism.

Original languageEnglish
JournalInternational Journal of Forecasting
Pages (from-to)733-747
Number of pages15
Publication statusPublished - 2018

    Research areas

  • Expected shortfall, Forecasting performance, GARCH, Large-scale study, MSGARCH, Risk management, Value-at-risk

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