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Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model
Investors often need to look for an optimal portfolio acting under ambiguity, as they may not be able to single out a unique real-world probability measure. In this paper a discrete-time dynamic portfolio selection problem is studied, referring to an [Formula: see text]-contaminated binomial market...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274693/ http://dx.doi.org/10.1007/978-3-030-50143-3_16 |
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author | Antonini, Paride Petturiti, Davide Vantaggi, Barbara |
author_facet | Antonini, Paride Petturiti, Davide Vantaggi, Barbara |
author_sort | Antonini, Paride |
collection | PubMed |
description | Investors often need to look for an optimal portfolio acting under ambiguity, as they may not be able to single out a unique real-world probability measure. In this paper a discrete-time dynamic portfolio selection problem is studied, referring to an [Formula: see text]-contaminated binomial market model and assuming investors’ preferences are consistent with the Choquet expected utility theory. We formulate the portfolio selection problem for a CRRA utility function in terms of the terminal wealth, and provide a characterization of the optimal solution in the case stock price returns are uniformly distributed. In this case, we further investigate the effect of the contamination parameter [Formula: see text] on the optimal portfolio. |
format | Online Article Text |
id | pubmed-7274693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72746932020-06-08 Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model Antonini, Paride Petturiti, Davide Vantaggi, Barbara Information Processing and Management of Uncertainty in Knowledge-Based Systems Article Investors often need to look for an optimal portfolio acting under ambiguity, as they may not be able to single out a unique real-world probability measure. In this paper a discrete-time dynamic portfolio selection problem is studied, referring to an [Formula: see text]-contaminated binomial market model and assuming investors’ preferences are consistent with the Choquet expected utility theory. We formulate the portfolio selection problem for a CRRA utility function in terms of the terminal wealth, and provide a characterization of the optimal solution in the case stock price returns are uniformly distributed. In this case, we further investigate the effect of the contamination parameter [Formula: see text] on the optimal portfolio. 2020-05-15 /pmc/articles/PMC7274693/ http://dx.doi.org/10.1007/978-3-030-50143-3_16 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Antonini, Paride Petturiti, Davide Vantaggi, Barbara Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title | Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title_full | Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title_fullStr | Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title_full_unstemmed | Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title_short | Dynamic Portfolio Selection Under Ambiguity in the [Formula: see text]-Contaminated Binomial Model |
title_sort | dynamic portfolio selection under ambiguity in the [formula: see text]-contaminated binomial model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274693/ http://dx.doi.org/10.1007/978-3-030-50143-3_16 |
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