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

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  • Alanya-Beltran, Willy

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.

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  • Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    • Handle: RePEc:eee:finlet:v:45:y:2022:i:c:s1544612321002026
    DOI: 10.1016/j.frl.2021.102121
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    Cited by:

    1. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.

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    More about this item

    Keywords

    Beta-t-EGARCH; Random shifts; Stock returns; Emerging markets;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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