Combining Alphas via Bounded Regression
Zura Kakushadze
Additional contact information
Zura Kakushadze: Quantigic® Solutions LLC, 1127 High Ridge Road #135, Stamford, CT 06905, USA
Risks, 2015, vol. 3, issue 4, 1-17
Abstract:
We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM) for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted) regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.
Keywords: hedge fund; alpha stream; alpha weights; portfolio turnover; investment allocation; weighted regression; diversification; bounds; optimization; factor models (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.mdpi.com/2227-9091/3/4/474/pdf (application/pdf)
https://www.mdpi.com/2227-9091/3/4/474/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:3:y:2015:i:4:p:474-490:d:58313
Access Statistics for this article
Risks is currently edited by Mr. Claude Zhang
More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().