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A Metropolis-in-Gibbs Sampler for Estimating Equity Market Factors

Author

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  • Sarantis Tsiaplias

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

Abstract

A model incorporating common Markovian regimes and GARCH residuals in a persistent factor environment is considered. Given the intractable and approximate nature of the likelihood function, a Metropolis-in-Gibbs sampler with Bayesian features is constructed for estimation purposes. The common factor drawing procedure is effectively an exact derivation of the Kalman filter with a Markovian regime component and GARCH innovations. To accelerate the drawing procedure, approximations to the conditional density of the common component are considered. The model is applied to equity data for 18 developed markets to derive global, European, and country specific equity market factors.

Suggested Citation

  • Sarantis Tsiaplias, 2007. "A Metropolis-in-Gibbs Sampler for Estimating Equity Market Factors," Melbourne Institute Working Paper Series wp2007n18, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    • Handle: RePEc:iae:iaewps:wp2007n18
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    File URL: http://melbourneinstitute.unimelb.edu.au/downloads/working_paper_series/wp2007n18.pdf
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    References listed on IDEAS

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    Cited by:

    1. Tsiaplias, Sarantis, 2008. "Factor estimation using MCMC-based Kalman filter methods," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 344-353, December.
    2. Sarantis Tsiaplias, 2007. "Co-movement and Integration among Developed Equity Markets," Melbourne Institute Working Paper Series wp2007n25, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    3. Sarantis Tsiaplias, 2007. "The Macroeconomic Content of Equity Market Factors," Melbourne Institute Working Paper Series wp2007n23, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

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    More about this item

    Keywords

    Common factors; Kalman filter; Markov switching; Monte Carlo; GARCH; Equities;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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