BAYESIAN LEARNING FOR THE MARKOWITZ PORTFOLIO SELECTION PROBLEM
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Publication:5207492
DOI10.1142/S0219024919500377zbMath1430.91084arXiv1811.06893WikidataQ127064930 ScholiaQ127064930MaRDI QIDQ5207492
Huyên Pham, Johann Nicolle, Carmine De Franco
Publication date: 2 January 2020
Published in: International Journal of Theoretical and Applied Finance (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1811.06893
Rationality and learning in game theory (91A26) Portfolio theory (91G10) PDEs in connection with game theory, economics, social and behavioral sciences (35Q91)
Related Items (4)
Discrete-Time Portfolio Optimization under Maximum Drawdown Constraint with Partial Information and Deep Learning Resolution ⋮ Effective approximation methods for constrained utility maximization with drift uncertainty ⋮ Continuous-time portfolio optimization for absolute return funds ⋮ Bayesian filtering for multi-period mean-variance portfolio selection
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