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Posterior Analysis of Stochastic Volatility Models with Flexible Tails

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  • Steel, M.F.J.

Abstract

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Suggested Citation

  • Steel, M.F.J., 1995. "Posterior Analysis of Stochastic Volatility Models with Flexible Tails," Papers 9568, Tilburg - Center for Economic Research.
  • Handle: RePEc:fth:tilbur:9568
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    Cited by:

    1. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    2. Gerlach, Richard & Tuyl, Frank, 2006. "MCMC methods for comparing stochastic volatility and GARCH models," International Journal of Forecasting, Elsevier, vol. 22(1), pages 91-107.
    3. Makieła, Kamil, 2016. "Bayesian inference in generalized true random-effects model and Gibbs sampling," MPRA Paper 69389, University Library of Munich, Germany.
    4. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    5. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    6. Barros, Carlos Pestana & Assaf, A.George & de Araujo, Ari Francisco, 2011. "Cost performance of Brazilian soccer clubs: A Bayesian varying efficiency distribution model," Economic Modelling, Elsevier, vol. 28(6), pages 2730-2735.
    7. repec:eee:touman:v:33:y:2012:i:5:p:1122-1127 is not listed on IDEAS

    More about this item

    Keywords

    FINANCIAL SECTOR;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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