PT - JOURNAL ARTICLE
AU - French, Ross
TI - Latent Factors in Equity Returns: How Many Are There and What Are They?
AID - 10.3905/jpm.2021.1.296
DP - 2021 Oct 06
TA - The Journal of Portfolio Management
PG - jpm.2021.1.296
4099 - http://jpm.pm-research.com/content/early/2021/10/06/jpm.2021.1.296.short
4100 - http://jpm.pm-research.com/content/early/2021/10/06/jpm.2021.1.296.full
AB - The optimal method for determining the number of latent factors in a dataset is an unresolved problem in explanatory factor analysis. This study uses several of the most commonly cited methods to determine the number of relevant factors in developed equity markets, finding that there are typically between 10 and 20. The results of these tests are evaluated against the optimal number of factors for estimating realized correlations. The author concludes that the information criteria and random matrix theory approaches provide the best results. Notwithstanding these results, they find that filtered correlation matrixes provide only a marginal advantage over the sample correlation matrix when estimating correlations. The study then examines economic interpretations of the latent factors, which adds context to the evaluation of the number. Finally, the author compares the efficacy of the modeled correlations in an important real-world application: minimum variance portfolio construction.Key Findings▪ There are 10–20 factors in developed equity markets: Factor 1 is the market factor, factors 2–4 are regional factors, and factors 5–20 are primarily geographic factors with a few industry-oriented factors also present.▪ Random matrix theory and information criteria provide accurate ex ante estimates of the number of latent factors in a dataset.▪ Filtered correlation matrixes do not provide a significant advantage over the sample correlation matrix in estimating future correlations.