Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 107, Issue 498, Pages 592-606Publisher
AMER STATISTICAL ASSOC
DOI: 10.1080/01621459.2012.682825
Keywords
Mean-variance efficiency; Portfolio improvement; Portfolio optimization; Risk assessment; Risk optimization; Short-sale constraint
Categories
Funding
- NSF [DMS-070433]
- National Institute of General Medical Sciences of NIH [R01-GM072611]
Ask authors/readers for more resources
This article introduces the large portfolio selection using gross-exposure constraints. It shows that with gross-exposure constraints, the empirically selected optimal portfolios based on estimated covariance matrices have similar performance to the theoretical optimal ones and there is no error accumulation effect from estimation of vast covariance matrices. This gives theoretical justification to the empirical results by Jagannathan and Ma. It also shows that the no-short-sale portfolio can be improved by allowing some short positions. The applications to portfolio selection, tracking, and improvements are also addressed. The utility of our new approach is illustrated by simulation and empirical studies on the 100 Fama-French industrial portfolios and the 600 stocks randomly selected from Russell 3000.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available