Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/210146
Authors: 
Basturk, Nalan
Borowska, Agnieszka
Grassi, Stefano
Hoogerheide, Lennart
van Dijk, Herman K.
Year of Publication: 
2018
Series/Report no.: 
Working Paper No. 10/2018
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 crosscorrelated 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 modelling and policy, in particular, from a risk-management perspective.
Persistent Identifier of the first edition: 
ISBN: 
978-82-8379-053-5
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.no
Document Type: 
Working Paper
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