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Constructing Bayesian tangency portfolios under short-selling restrictions
Örebro University, Örebro University School of Business. Unit of Statistics.ORCID iD: 0000-0003-1359-3311
Department of Mathematics, Stockholm University, Stockholm, Sweden.
Department of Mathematics, Stockholm University, Stockholm, Sweden.
2024 (English)In: Finance Research Letters, ISSN 1544-6123, E-ISSN 1544-6131, Vol. 62, article id 105065Article in journal (Refereed) Published
Abstract [en]

We address the challenge of constructing tangency portfolios in the context of short-selling restrictions. Utilizing Bayesian techniques, we reparameterize the asset return model, enabling direct determination of priors for the tangency portfolio weights. This facilitates the integration of non-negative weight constraints into an investor's prior beliefs, resulting in a posterior distribution focused exclusively on non-negative values. Portfolio weight estimators are subsequently derived via the Markov Chain Monte Carlo (MCMC) methodology. Our novel Bayesian approach is empirically illustrated using the most significant stocks in the S&P 500 index. The method showcases promising results in terms of risk-adjusted returns and interpretability.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 62, article id 105065
Keywords [en]
Bayesian inference, Tangency portfolio, MCMC, Parameter uncertainty
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-112586DOI: 10.1016/j.frl.2024.105065ISI: 001181756900001Scopus ID: 2-s2.0-85183988859OAI: oai:DiVA.org:oru-112586DiVA, id: diva2:1846797
Available from: 2024-03-25 Created: 2024-03-25 Last updated: 2024-03-25Bibliographically approved

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Bodnar, Olha

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