Abstract

http://ssrn.com/abstract=1347648
 
 

References (10)



 
 

Citations (8)



 


 



The Augmented Black-Litterman Model: A Ranking-Free Approach to Factor-Based Portfolio Construction and Beyond


Wing Cheung


affiliation not provided to SSRN

August 30, 2007

Quantitative Finance, DOI: 10.1080/14697688.2012.714902

Abstract:     
The Fama and French (1992 and 1993 etc.) factor ranking approach is very popular among quantitative fund managers. However, this approach suffers from hidden factor view, loss of information, etc. issues. Based on the Black-Litterman model (Black and Litterman, 1992; as explained in Cheung, 2009A), we design a technique that endogenises the ranking process and elegantly resolves these issues. This model explicitly seeks forward-looking factor views and smoothly blends them to deliver robust allocation to securities. Our numerical experiments show this is an intuitive and practical framework for factor-based portfolio construction, and beyond.

The paper is featured by:
- A new and unified framework for strategy combination, factor mimicking and security-specific bets
- An elegant and ranking-free approach to factor style construction
- Worked examples based on the FTSE EUROTOP 100 universe
- Insight into the classic issue of confidence parameter setting
- An implementation guidance in the appendix

Number of Pages in PDF File: 28

Keywords: asset allocation, portfolio construction, Bayes' Rule, Black-Litterman, view blending and shrinkage, CAPM, semi-strong market efficiency, Fama-French, factor ranking, factor risk model, mean-variance optimisation, robustness

JEL Classification: C10, C11, C61, G11, G14

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Date posted: February 26, 2009 ; Last revised: October 21, 2012

Suggested Citation

Cheung, Wing, The Augmented Black-Litterman Model: A Ranking-Free Approach to Factor-Based Portfolio Construction and Beyond (August 30, 2007). Quantitative Finance, DOI: 10.1080/14697688.2012.714902. Available at SSRN: http://ssrn.com/abstract=1347648 or http://dx.doi.org/10.2139/ssrn.1347648

Contact Information

Wing Cheung (Contact Author)
affiliation not provided to SSRN
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