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Estimation of the Cholesky Multivariate Stochastic Volatility Model Using Iterated Filtering

Author

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  • Szczepocki Piotr

    (1 University of Lodz, Lodz, Poland)

Abstract

The paper aims to propose a new estimation method for the Cholesky Multivariate Stochastic Volatility Model based on the iterated filtering algorithm (Ionides et al., 2006, 2015).

Suggested Citation

  • Szczepocki Piotr, 2023. "Estimation of the Cholesky Multivariate Stochastic Volatility Model Using Iterated Filtering," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 27(4), pages 44-58, December.
    • Handle: RePEc:vrs:eaiada:v:27:y:2023:i:4:p:44-58:n:4
    DOI: 10.15611/eada.2023.4.04
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    References listed on IDEAS

    as
    1. Bhadra, Anindya & Ionides, Edward L. & Laneri, Karina & Pascual, Mercedes & Bouma, Menno & Dhiman, Ramesh C., 2011. "Malaria in Northwest India: Data Analysis via Partially Observed Stochastic Differential Equation Models Driven by Lévy Noise," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 440-451.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    multivariate stochastic volatility; iterated filtering; particle filters; the Cholesky Multivariate Stochastic Volatility (ChMSV) Model;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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