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Comparing and evaluating Bayesian predictive distributions of asset returns

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Author Info
John Geweke () (Departments of Statistics and Economics, University of Iowa, 430 N. Clinton St., Iowa City, IA 52242-2020, USA.)
Gianni Amisano () (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.)

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Abstract

Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative models of asset returns applied to daily S&P 500 returns from 1976 through 2005. The comparison exercise uses predictive likelihoods and is inherently Bayesian. The evaluation exercise uses the probability integral transform and is inherently frequentist. The illustration shows that the two approaches can be complementary, each identifying strengths and weaknesses in models that are not evident using the other. JEL Classification: C11, C53.

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Publisher Info
Paper provided by European Central Bank in its series Working Paper Series with number 969.

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Length: 33 pages
Date of creation: Nov 2008
Date of revision:
Handle: RePEc:ecb:ecbwps:20080969

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Related research
Keywords: Forecasting; GARCH; inverse probability transform; Markov mixture; predictive likelihood; S&P 500 returns; stochastic volatility.;

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References listed on IDEAS
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  4. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244. [Downloadable!]
    Other versions:
  5. John Geweke & Gianni Amisano, 2008. "Optimal Prediction Pools," Working Paper Series 22-08, Rimini Centre for Economic Analysis, revised Jan 2008. [Downloadable!]
    Other versions:
  6. Gianni Amisano & Raffaella Giacomini, 2005. "Comparing Density Forecsts via Weighted Likelihood Ratio Tests," Working Papers ubs0504, University of Brescia, Department of Economics. [Downloadable!]
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  7. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society. [Downloadable!]
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  8. Stéphane Adjemian & Matthieu Darracq Pariès & Stéphane Moyen, 2008. "Towards a monetary policy evaluation framework," Working Paper Series 942, European Central Bank. [Downloadable!]
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  11. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November. [Downloadable!] (restricted)
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