Optimal constrained strategies for factor-based investing in the Brazilian stock market

Abstract

The paper examines investment strategies for factor-based portfolios formed by integrating a regime-switching model with a stochastic recursive utility function. Drawing from the seminal works of Fama and French (1993) and Carhart (1997), the authors identify four risk factors within the Brazilian stock market. Subsequently, employing the CGL model proposed by Campani et al. (2021), the study develops investment strategies to diversify across portfolios formed with these risk factors. The CGL model provides the framework to apply the stochastic recursive utility function to estimate the strategies based on regimes, from which the authors implement dynamic constraints to optimally control the portfolio weights. They then conduct a performance analysis through an out-of-sample exercise to compare the regime-switching strategies with benchmarks formed by single-state passive and active strategies. The empirical findings demonstrate the outperformance of regime-switching strategies, as evidenced by superior Sharpe ratios across both the complete sample and shorter subsamples within the exercise. The results also reveal that the unleveraged regime-switching strategy consistently exhibits the lowest volatility within each sample subset. In addition, the analysis of certainty equivalent returns confirms the statistical significance of the outperformance of regime-switching strategies over the benchmarks. The investigation focused on the Brazilian stock market to examine the potential benefits and efficacy of applying such a strategy in an emerging market context. Ultimately, the findings underscore that factor-based strategies formulated through a regime-switching model using a stochastic recursive utility function have the potential to outperform traditional benchmarks in terms of risk-adjusted returns within the Brazilian stock market, offering actionable insights for investors navigating the Brazilian landscape.