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Generalised density forecast combinations

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  • Fawcett, Nicholas

    ()
    (Bank of England)

  • Kapetanios, George

    ()
    (Queen Mary University of London)

  • Mitchell, James

    ()
    (WBS)

  • Price, Simon

    ()
    (Bank of England)

Abstract

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is trying to forecast. Specific attention is paid to the use of piecewise linear weight functions that let the weights vary by region of the density. We analyse these schemes theoretically, in Monte Carlo experiments and in an empirical study. Our results show that the generalised combinations outperform their linear counterparts.

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Bibliographic Info

Paper provided by Bank of England in its series Bank of England working papers with number 492.

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Length: 41 pages
Date of creation: 28 Mar 2014
Date of revision:
Handle: RePEc:boe:boeewp:0492

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Keywords: Density Forecasting; Model Combination; Scoring Rules;

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