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Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?

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  • Hoogerheide, Lennart F.
  • Ardia, David
  • Corré, Nienke

Abstract

Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between qualities of whole density forecasts, whereas the Bayesian approach exhibits significantly better left-tail forecast accuracy.

Suggested Citation

  • Hoogerheide, Lennart F. & Ardia, David & Corré, Nienke, 2012. "Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?," Economics Letters, Elsevier, vol. 116(3), pages 322-325.
    • Handle: RePEc:eee:ecolet:v:116:y:2012:i:3:p:322-325
    DOI: 10.1016/j.econlet.2012.03.026
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    Cited by:

    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.

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    More about this item

    Keywords

    GARCH; Bayesian; KLIC; Censored likelihood;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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