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Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation

Author

Listed:
  • Leona Han Chen

    (Hunan University)

  • Yijie Fei

    (Hunan University)

  • Jun Yu

    (University of Macau)

Abstract

Modeling multivariate stochastic volatility (MSV) can pose significant challenges, particularly when both variances and covariances are time-varying. In this study, we tackle these complexities by introducing novel MSV models based on the generalized Fisher transformation (GFT) proposed by Archakov and Hansen (2021). Our model exhibits remarkable flexibility, ensuring the positive-definiteness of the variancecovariance matrix, and disentangling the driving forces of volatilities and correlations. To conduct Bayesian analysis of the models, we employ a Particle Gibbs Ancestor Sampling (PGAS) method, facilitating efficient Bayesian model comparisons. Furthermore, we extend our MSV model to cover leverage effects and incorporate realized measures. Our simulation studies demonstrate that the proposed method performs well for our GFT-based MSV model. Furthermore, empirical studies based on equity returns show that the MSV models outperform alternative specifications in both in-sample and outof-sample performances.

Suggested Citation

  • Leona Han Chen & Yijie Fei & Jun Yu, 2024. "Multivariate Stochastic Volatility Models based on Generalized Fisher Transformation," Working Papers 202419, University of Macau, Faculty of Business Administration.
    • Handle: RePEc:boa:wpaper:202419
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    File URL: https://fba.um.edu.mo/wp-content/uploads/RePEc/doc/202419.pdf
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    More about this item

    Keywords

    Multivariate stochastic volatility; Dynamic correlation; Leverage effect; Particle filter; Markov chain Monte Carlo; Realized measures;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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