Template-Type: ReDIF-Paper 1.0 Series: Tinbergen Institute Discussion Papers Creation-Date: 2011-01-31 Number: 11-020/4 Author-Name: Lennart F. Hoogerheide Author-Email: firstname.lastname@example.org Author-Workplace-Name: Erasmus University Rotterdam Author-Name: David Ardia Author-Email: David.Ardia@aeris-capital.com Author-Workplace-Name: aeris CAPITAL Author-Name: Nienke Corre Title: Stock Index Returns' Density Prediction using GARCH Models: Frequentist or Bayesian Estimation? Abstract: This discussion paper resulted in an article in Economics Letters, 2012, 116(3), 322-325.
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. Classification-JEL: C11, C52, C53, C58 Keywords: GARCH, Bayesian, KLIC, censored likelihood File-Url: http://papers.tinbergen.nl/11020.pdf File-Format: application/pdf File-Size: 120281 bytes Handle: RePEc:tin:wpaper:20110020