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Type | Journal Article |
Scope | Discipline-based scholarship |
Title | Uncertainty in the black-litterman model: empirical estimation of the equilibrium |
Organization Unit | |
Authors |
|
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Journal Title | Journal of Empirical Finance |
Publisher | Elsevier |
Geographical Reach | international |
ISSN | 0927-5398 |
Volume | 72 |
Page Range | 251 - 275 |
Date | 2023 |
Abstract Text | The Black-Litterman model is a widely used and well established application of the Bayesian framework to asset allocation problems. It is, however, difficult to calibrate, as it requires the specification of abstract uncertainty parameters. We propose a new, more flexible model that allows the empirical estimation of the equilibrium, alleviating the need for parametrization. In an empirical application, we illustrate the sensitivity of the classical Black-Litterman model to the choice of the uncertainty parameter. We then demonstrate that the flexible model successfully exploits information in the cross-section of index constituents’ returns to find an optimal trade-off in calibration of the uncertainty. |
Free access at | DOI |
Digital Object Identifier | 10.1016/j.jempfin.2023.03.009 |
Other Identification Number | merlin-id:23875 |
PDF File | Download from ZORA |
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