Lewin Marcelo, Campani Carlos Heitor
COPPEAD Graduate School of Business (Federal University of Rio de Janeiro), Rua Pascoal Lemme 355, Cidade Universitaria, Rio de Janeiro, RJ 21941-918 Brazil.
Edhec Risk Institute, Nice, France.
Financ Mark Portf Mang. 2023;37(1):27-59. doi: 10.1007/s11408-022-00414-x. Epub 2022 Jun 24.
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.
The online version contains supplementary material available at 10.1007/s11408-022-00414-x.
我们通过一个政权切换模型实施一种分配策略，该模型在考虑交易成本的样本外练习中使用递归效用偏好。我们研究投资组合的换手率和杠杆率，提出两种程序来约束分配策略：低换手率控制（LoT）和最大杠杆控制（MaxLev）。LoT设置一个动态阈值以减少小幅再平衡，降低投资组合换手率，减轻成本。MaxLev计算对风险厌恶参数的动态调整以约束投资组合杠杆率。MaxLev调整取决于风险厌恶和允许的投资组合杠杆率，这使得能够考虑杠杆约束的最优策略。该研究使用美国股票投资组合，并表明，首先，当交易成本增加时，采用LoT的模型比未采用的模型具有更优的风险回报指标。其次，考虑交易成本时，使用MaxLev的模型的风险回报指标与相应的无约束政权切换基准指标紧密匹配或超过后者。第三，MaxLev回报的波动性更低，风险回报比传统数值约束基准更高。第四，确定性等价回报表明，使用MaxLev和LoT的模型在统计上显著优于单状态模型和无约束政权切换模型。
在线版本包含可在10.1007/s11408-022-00414-x获取的补充材料。
