Constrained portfolio strategies in a regime-switching economy

Marcelo Lewin () and Carlos Heitor Campani ()
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Marcelo Lewin: COPPEAD Graduate School of Business (Federal University of Rio de Janeiro)
Carlos Heitor Campani: COPPEAD Graduate School of Business (Federal University of Rio de Janeiro)

Financial Markets and Portfolio Management, 2023, vol. 37, issue 1, No 2, 27-59

Abstract: 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.

Keywords: Regime switching models; Dynamic asset allocation; Stochastic differential recursive utility; Analytical solutions; Transaction costs; Leverage and turnover constraints (search for similar items in EconPapers)
JEL-codes: C02 E44 G11 G24 O16 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11408-022-00414-x

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