Low risk, high variability: Practical guide for portfolio construction

The low-risk anomaly challenges traditional financial theory by stating that less volatile stocks generate higher risk-adjusted returns. This paper explores how various portfolio construction choices influence the performance of low-risk portfolios. We show that methodological decisions critically influence portfolio outcomes, causing substantial dispersion in performance metrics across weighting schemes and risk estimators. This can only be marginally mitigated by incorporating constraints such as short-sale restrictions and size or price filters. Our analysis reveals that volatility-based estimators yield the most favorable performance distribution, outperforming beta-based approaches. Transaction costs are found to significantly affect performance and are vitally important in identifying the most attractive portfolios, highlighting the importance of realistic implementation constraints. Through rigorous empirical analysis, this study bridges the gap between theoretical insights and practical applications, offering actionable guidance to investors. The findings advocate for a cautious approach to nonstandard errors in portfolio modeling and emphasize the necessity of robust strategies in low-risk investing.