English, Article, Journal or magazine article edition: Forecast accuracy and economic gains from Bayesian model averaging using time varying weight Lennart Hoogerheide; Richard Kleijn; Francesco Ravazzolo; ...

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Bookmark: http://trove.nla.gov.au/version/4761
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Forecast accuracy and economic gains from Bayesian model averaging using time varying weight
Author
  • Lennart Hoogerheide
  • Richard Kleijn
  • Francesco Ravazzolo
  • Herman K. van Dijk
  • Marno Verbeek
Physical Description
  • preprint
Notes
  • Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using ¯nancial and macroeconomic time series. The results indicate that the proposed time varying model weight schemes outperform other combination schemes in terms of predictive and economic gains. In an empirical application using returns on the S&​P 500 index, time varying model weights provide improved forecasts with substantial economic gains in an investment strategy including transaction costs. Another empirical example refers to forecasting US economic growth over the business cycle. It suggests that time varying combination schemes may be very useful in business cycle analysis and forecasting, as these may provide an early indicator for recessions.
  • Forecast combination, Bayesian model averaging, time varying model weights, portfolio optimization, business cycle
  • RePEc:bno:worpap:2009_10
Language
  • English
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