Abstract
In quantitative equity fund management, the popular traditional method to gain factor exposures is to perform factor ranking. This method easily leads to some crowded ‘style islands’, where numerous fund managers trade similar portfolios. The Bayesian allocation technique creates more efficient factor-mimicking (FM) portfolios (as evident in Cheung and Mittal, 2009), and these factor style portfolios tend to be more diversified. To further distance ourselves from crowded trades, one may utilise the blending capability of the Bayesian allocation framework to span the space between those islands. More differentiation benefits could also be obtained by customising the factor models. In this article, crowdedness is quantified by the Nomura trade impact cost model, METRIC. Based on this, we show evidence of the potential benefit from applying the new portfolio construction framework. This article features: - Trading cost comparison between factor ranking and Bayesian FM portfolios in simulated crowding events; and - Evidence of cost reduction by switching from the factor-ranking to ABL portfolio construction process.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
