{"title":"Constrained portfolio strategies in a regime-switching economy.","authors":"Marcelo Lewin, Carlos Heitor Campani","doi":"10.1007/s11408-022-00414-x","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11408-022-00414-x.</p>","PeriodicalId":44895,"journal":{"name":"Financial Markets and Portfolio Management","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243879/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Financial Markets and Portfolio Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11408-022-00414-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The journal Financial Markets and Portfolio Management invites submissions of original research articles in all areas of finance, especially in – but not limited to – financial markets, portfolio choice and wealth management, asset pricing, risk management, and regulation. Its principal objective is to publish high-quality articles of innovative research and practical application. The readers of Financial Markets and Portfolio Management are academics and professionals in finance and economics, especially in the areas of asset management. FMPM publishes academic and applied research articles, shorter ''Perspectives'' and survey articles on current topics of interest to the financial community, as well as book reviews. All article submissions are subject to a double-blind peer review. http://www.fmpm.org
Officially cited as: Financ Mark Portf Manag