Asymmetry in stochastic volatility models with threshold and time-dependent correlation

Schäfers Torben and Teng Long ()
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Schäfers Torben: Lehrstuhl für Angewandte Mathematik und Numerische Analysis, Fakultät für Mathematik und Naturwissenschaften, Bergische Universität Wuppertal, Gaußstr. 20, 42119, Wuppertal, Germany
Teng Long: Lehrstuhl für Angewandte Mathematik und Numerische Analysis, Fakultät für Mathematik und Naturwissenschaften, Bergische Universität Wuppertal, Gaußstr. 20, 42119, Wuppertal, Germany

Studies in Nonlinear Dynamics & Econometrics, 2023, vol. 27, issue 2, 131-146

Abstract: In this work we study the effects by including threshold, constant and time-dependent correlation in stochastic volatility (SV) models to capture the asymmetry relationship between stock returns and volatility. We develop SV models which include only time-dependent correlated innovations and both threshold and time-dependent correlation, respectively. It has been shown in literature that the SV model with only constant correlation does a better job of capturing asymmetry than threshold stochastic volatility (TSV) model. We show here that the SV model with time-dependent correlation performs better than the model with constant correlation on capturing asymmetry, and the comprehensive model with both threshold and time-dependently correlated innovations dominates models with pure threshold, constant and time-dependent correlation, and both threshold and constant correlation as well. In our comprehensive model, volatility and returns are time-dependently correlated, where the time-varying correlation is negative, and the volatility is more persistent, less volatile and higher following negative returns as expected. An empirical study is provided to illustrate our findings.

Keywords: asymmetry volatility; stochastic volatility model; threshold; time-dependent correlation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/snde-2021-0020

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