Despite extensive research support, the role of diversification in current factor investing strategies remains neglected. This paper investigates whether well-designed multifactor portfolios should not only be based on firm characteristics, but should also include portfolio diversification effects. While the alpha concentration approach mainly considers factor-specific firm characteristics, the diversified approach utilizes covariance estimators in addition to firm characteristics to account for portfolio diversification. The corresponding out-of-sample results show that including an efficient covariance estimator improves the performance of long-only multifactor portfolios compared to the pure alpha concentration approach. A particular advantage of diversified factor investing strategies can be identified in the significant increase in exposure to the low-volatility factor represented by firm characteristics with high informational content. No significant performance differences are observed for long-short portfolios where the factor exposures of the alpha concentration and diversification approaches are similar with respect to the low-volatility factor.

尽管有广泛的研究支持，多元化在当前因子投资策略中的作用仍然被忽视。本文探讨了设计良好的多因子投资组合是否不仅应基于公司特征，还应包括投资组合多元化效应。虽然阿尔法集中法主要考虑特定因素的公司特征，但多元化方法除了公司特征外还利用协方差估计量来解释投资组合的多样化。相应的样本外结果表明，与纯 alpha 集中方法相比，包括一个有效的协方差估计器可以提高只做多的多因子投资组合的性能。多元化因子投资策略的一个特殊优势可以体现在显着增加对以具有高信息含量的公司特征为代表的低波动性因子的敞口。对于多空投资组合，没有观察到显着的性能差异，其中 alpha 集中和多元化方法的因子敞口在低波动率因子方面相似。