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Portfolio Optimization with Active, Passive, and Factors: Removing the Ad Hoc Step

Authors: Roger Aliaga-Diaz; Giulio Renzi-Ricci; Ankul Daga; Harshdeep Ahluwalia;

Portfolio Optimization with Active, Passive, and Factors: Removing the Ad Hoc Step

Abstract

In this article, the authors propose a comprehensive framework for simultaneously allocating assets among active, passive, and factor investments while accounting for the uncertainty in each of the sources of return and investor risk preferences toward them. The proposed model enables investors to overcome the often adopted approach of first deciding the asset allocation and subsequently allocating across active and factor strategies. The authors also highlight some business applications of the adopted approach, such as the construction of factor tilted portfolios and the substitution of low-cost factor strategies for higher cost active portfolios. TOPICS:Analysis of individual factors/risk premia, factor-based models, portfolio theory, portfolio construction Key Findings • Using an expected utility optimization model, the authors can simultaneously allocate assets among active, passive, and factor investments while accounting for investor risk preferences. • Optimal asset allocation responds to changes in the level of risk aversion across systematic, alpha, and factor risk; expected factor-adjusted alpha levels; tracking errors; and predicted factor premiums. • This approach allows for full customization of portfolios and brings to light many decisions that investors would otherwise make subconsciously.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
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