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

Lennart Hoogerheide, David Ardia & Nienke Corré

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.
   
Keywords GARCH; Bayesian; KLIC; Censored likelihood
   
Citation Hoogerheide, L., Ardia, D., & Corré, N. (2012). Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation?. Economics Letters, 116(3), 322-325.
   
Type Journal article (English)
Date of appearance 2012
Journal Economics Letters
Volume 116
Issue 3
Pages 322-325
URL http://www.sciencedirect.com/science/article/pii/S0165176...