%0 Journal Article
%A Mladina, Peter
%A Moore, David
%T Detecting Factor Risk in Private Asset Returns
%D 2019
%R 10.3905/jpm.2019.1.113
%J The Journal of Portfolio Management
%P jpm.2019.1.113
%X The authors introduce a novel approach of attributing factor risk to a time series of reported private asset returns. Their factor-optimized lagged-beta (FOLB) method uncovers more latent factor risk than standard unsmoothing techniques, offering a more precise attribution of factor betas and alpha for major categories of private assets, including buyout, venture capital, and private real estate. They find that factor-adjusted alpha is most robust for buyout, though results vary somewhat by factor-model specification. The FOLB method enhances portfolio management by providing improved estimates of factor risk and alpha for private asset classes, an optimal factor benchmark for asset allocation modeling and manager performance benchmarking, and new procedures for unsmoothing reported private asset returns to estimate risk parameters for portfolio optimization.TOPICS: Analysis of individual factors/risk premia, factor-based models, style investingKey Findings• The factor-optimized lagged-beta method offers improved estimates of factor risk and alpha for private asset classes.• Factor-adjusted alpha is most robust for buyout.• The method provides an optimal factor benchmark for asset allocation modeling and manager performance benchmarking and new procedures for unsmoothing reported private asset returns to estimate risk parameters for portfolio optimization.
%U https://jpm.pm-research.com/content/iijpormgmt/early/2019/10/30/jpm.2019.1.113.full.pdf