Modelling stock returns volatility with dynamic conditional score models and random shifts

Willy Alanya-Beltran

Finance Research Letters, 2022, vol. 45, issue C

Abstract: I propose and study a dynamic conditional score model with random shifts, the RS-Beta-t-EGARCH model, for modelling volatility in financial markets. The addition of random shifts can explain the high volatility persistence typically estimated for these financial series. This setting constitutes an alternative approach to long memory models; moreover, the new model identifies volatility clusters. I apply the model to stock returns in South American emerging markets. The estimates for the random shifts fit the main regime disturbance events in the period of study. Monte Carlo simulations show that the new model replicates the time and spectral domain properties of the original series. Finally, out-sample forecast evidence favors the new specification.

Keywords: Beta-t-EGARCH; Random shifts; Stock returns; Emerging markets (search for similar items in EconPapers)
JEL-codes: C12 C53 C58 G12 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:45:y:2022:i:c:s1544612321002026

DOI: 10.1016/j.frl.2021.102121

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