A simulation study on the Markov regime-switching zero-drift GARCH model

Yanlin Shi ()
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Yanlin Shi: Macquarie University

Annals of Operations Research, 2023, vol. 330, issue 1, No 1, 20 pages

Abstract: Abstract A Zero-drift GARCH (ZD-GARCH) model is recently proposed to study conditional and unconditional heteroskedasticity together. Despite its attractive statistical properties, our research demonstrates that the stability test based on this model fails when structural changes are present. To overcome this issue, we allow the Markov regime-switching (MRS) feature within the ZD-GARCH framework and propose an MRS-ZD-GARCH model. A revised stability estimator is further derived. The effectiveness of our proposed approach to test the stability with and without structural changes is evidenced via simulation studies. Using the empirical data of the S&P 500, NASDAQ and Apple returns, we show that the new model can also outperform the ZD-GARCH model in practice and provide more informative results. Therefore, the MRS-ZD-GARCH model could be a widely useful tool to study the stability of financial data and help address risk management issues in other contexts.

Keywords: Volatility modelling; Zero-drift GARCH; Regime switching; Heteroskedasticity (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-020-03832-0

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