Within-regime volatility dynamics for observable- and Markov-switching score-driven models

Szabolcs Blazsek, Dejun Kong and Samantha R. Shadoff

Finance Research Letters, 2025, vol. 73, issue C

Abstract: We study the novel Markov-switching (MS) Beta-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model, using within-regime volatility dynamics, similar to the recent observable-switching (OS) Beta-t-EGARCH model. We report in-sample results on the Standard & Poor’s 500 (S&P 500) and a random sample of 50 firms from the S&P 500 from March 1986 to July 2024. We compare the out-of-sample forecasting performances of OS-Beta-t-EGARCH and MS-Beta-t-EGARCH from May 2005 to July 2024 and confirm that OS-Beta-t-EGARCH is superior to MS-Beta-t-EGARCH.

Keywords: Dynamic conditional score (DCS); Generalized autoregressive score (GAS); Regime-switching volatility models; Standard & Poor’s 500 (S&P 500) (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:73:y:2025:i:c:s154461232401660x

DOI: 10.1016/j.frl.2024.106631

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