Baştürk, N., Borowska, A. , Grassi, S., Hoogerheide, L. and van Dijk, H.K. (2019) Forecast density combinations of dynamic models and data driven portfolio strategies. Journal of Econometrics, 210, pp. 170-186. (doi: 10.1016/j.jeconom.2018.11.011)
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Abstract
A dynamic asset-allocation model is specified in probabilistic terms as a combination of return distributions resulting from multiple pairs of dynamic models and portfolio strategies based on momentum patterns in US industry returns. The nonlinear state space representation of the model allows efficient and robust simulation-based Bayesian inference using a novel non-linear filter. Combination weights can be cross-correlated and correlated over time using feedback mechanisms. Diagnostic analysis gives insight into model and strategy misspecification. Empirical results show that a smaller flexible model-strategy combination performs better in terms of expected return and risk than a larger basic model-strategy combination. Dynamic patterns in combination weights and diagnostic learning provide useful signals for improved modeling and policy, in particular, from a risk-management perspective.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Borowska, Dr Agnieszka |
Authors: | Baştürk, N., Borowska, A., Grassi, S., Hoogerheide, L., and van Dijk, H.K. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
Journal Name: | Journal of Econometrics |
Publisher: | Elsevier |
ISSN: | 0304-4076 |
ISSN (Online): | 1872-6895 |
Published Online: | 12 November 2018 |
Copyright Holders: | Copyright © 2018 Elsevier B.V. |
First Published: | First published in Journal of Econometrics 210:170-186 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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