Selecting volatility forecasting models for portfolio allocation purposes
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Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.
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|Item Type:||Journal Article|
|Keywords:||multivariate time series, loss functions, evaluating forecasts, covariance matrix, GARCH models, model cofidence set|
|Divisions:||Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
|Copyright Owner:||Copyright 2014 International Institute of Forecasters|
|Copyright Statement:||NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, [VOL 31, ISSUE 3, (2015)] DOI: 10.1016/j.ijforecast.2013.11.007|
|Deposited On:||30 Apr 2014 22:45|
|Last Modified:||02 Aug 2015 13:38|
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