Kapetanios, G and Mitchell, J and Price, S and Fawcett, N (2015) Generalised density forecast combinations. Journal of Econometrics, 188 (1). pp. 150-165. DOI https://doi.org/10.1016/j.jeconom.2015.02.047
Kapetanios, G and Mitchell, J and Price, S and Fawcett, N (2015) Generalised density forecast combinations. Journal of Econometrics, 188 (1). pp. 150-165. DOI https://doi.org/10.1016/j.jeconom.2015.02.047
Kapetanios, G and Mitchell, J and Price, S and Fawcett, N (2015) Generalised density forecast combinations. Journal of Econometrics, 188 (1). pp. 150-165. DOI https://doi.org/10.1016/j.jeconom.2015.02.047
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.
Item Type: | Article |
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Additional Information: | Source info: Bank of England Working Paper No. 492 |
Uncontrolled Keywords: | Density forecasting; Model combination; Scoring rules |
Subjects: | H Social Sciences > HG Finance |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 22 Nov 2016 10:49 |
Last Modified: | 29 Oct 2024 08:12 |
URI: | http://repository.essex.ac.uk/id/eprint/18196 |