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Stock Index Returns' Density Prediction using GARCH Models: Frequentist or Bayesian Estimation?

This discussion paper resulted in an article in <I>Economics Letters</I> (2012). Vol. 116(3), 322-325.<p> Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts of the whole density, whereas the Bayesian approach exhibits significantly better left-tail forecast accuracy.
Year of publication:
2011-01-31
Authors: Hoogerheide, Lennart F. ; Ardia, David ; Corre, Nienke
Institutions: Tinbergen Instituut
Subject: GARCH | Bayesian | KLIC | censored likelihood
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Type of publication: Book / Working Paper
Notes:
The text is part of a series Tinbergen Institute Discussion Papers Number 11-020/4
Classification: C11 - Bayesian Analysis ; C52 - Model Evaluation and Testing ; C53 - Forecasting and Other Model Applications ; c58
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Persistent link: https://www.econbiz.de/10011256766
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