Cargando…
Constrained portfolio strategies in a regime-switching economy
We implement an allocation strategy through a regime-switching model using recursive utility preferences in an out-of-sample exercise accounting for transaction costs. We study portfolios turnover and leverage, proposing two procedures to constrain the allocation strategies: a low-turnover control (...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243879/ https://www.ncbi.nlm.nih.gov/pubmed/35789919 http://dx.doi.org/10.1007/s11408-022-00414-x |
_version_ | 1784738408506064896 |
---|---|
author | Lewin, Marcelo Campani, Carlos Heitor |
author_facet | Lewin, Marcelo Campani, Carlos Heitor |
author_sort | Lewin, Marcelo |
collection | PubMed |
description | We implement an allocation strategy through a regime-switching model using recursive utility preferences in an out-of-sample exercise accounting for transaction costs. We study portfolios turnover and leverage, proposing two procedures to constrain the allocation strategies: a low-turnover control (LoT) and a maximum leverage control (MaxLev). LoT sets a dynamic threshold to trim minor rebalancing, reducing portfolio turnover, mitigating costs. MaxLev calculates dynamic adjustments to the risk aversion parameter to constrain the portfolio leverage. The MaxLev adjustments depend on the risk aversion and permitted portfolio leverage, which enables optimal strategies considering the leverage constraints. The study uses US equity portfolios, and shows that, first, models with LoT result in superior return-to-risk measures than those without it when transaction costs increase. Second, considering transaction costs, the return-to-risk measures of the models using MaxLev closely match or exceed those from the corresponding unconstrained regime-switching benchmarks. Third, MaxLev returns have lower volatility and higher return-to-risk than conventional numerically constrained benchmarks. Fourth, the certainty equivalent returns indicate that models using MaxLev and LoT outperform both single-state models and unconstrained regime-switching models with statistical significance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11408-022-00414-x. |
format | Online Article Text |
id | pubmed-9243879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92438792022-06-30 Constrained portfolio strategies in a regime-switching economy Lewin, Marcelo Campani, Carlos Heitor Financ Mark Portf Mang Article We implement an allocation strategy through a regime-switching model using recursive utility preferences in an out-of-sample exercise accounting for transaction costs. We study portfolios turnover and leverage, proposing two procedures to constrain the allocation strategies: a low-turnover control (LoT) and a maximum leverage control (MaxLev). LoT sets a dynamic threshold to trim minor rebalancing, reducing portfolio turnover, mitigating costs. MaxLev calculates dynamic adjustments to the risk aversion parameter to constrain the portfolio leverage. The MaxLev adjustments depend on the risk aversion and permitted portfolio leverage, which enables optimal strategies considering the leverage constraints. The study uses US equity portfolios, and shows that, first, models with LoT result in superior return-to-risk measures than those without it when transaction costs increase. Second, considering transaction costs, the return-to-risk measures of the models using MaxLev closely match or exceed those from the corresponding unconstrained regime-switching benchmarks. Third, MaxLev returns have lower volatility and higher return-to-risk than conventional numerically constrained benchmarks. Fourth, the certainty equivalent returns indicate that models using MaxLev and LoT outperform both single-state models and unconstrained regime-switching models with statistical significance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11408-022-00414-x. Springer US 2022-06-24 2023 /pmc/articles/PMC9243879/ /pubmed/35789919 http://dx.doi.org/10.1007/s11408-022-00414-x Text en © The Author(s) under exclusive licence to Swiss Society for Financial Market Research 2022 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 Lewin, Marcelo Campani, Carlos Heitor Constrained portfolio strategies in a regime-switching economy |
title | Constrained portfolio strategies in a regime-switching economy |
title_full | Constrained portfolio strategies in a regime-switching economy |
title_fullStr | Constrained portfolio strategies in a regime-switching economy |
title_full_unstemmed | Constrained portfolio strategies in a regime-switching economy |
title_short | Constrained portfolio strategies in a regime-switching economy |
title_sort | constrained portfolio strategies in a regime-switching economy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243879/ https://www.ncbi.nlm.nih.gov/pubmed/35789919 http://dx.doi.org/10.1007/s11408-022-00414-x |
work_keys_str_mv | AT lewinmarcelo constrainedportfoliostrategiesinaregimeswitchingeconomy AT campanicarlosheitor constrainedportfoliostrategiesinaregimeswitchingeconomy |