Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/167865 
Year of Publication: 
2015
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 3 [Issue:] 4 [Publisher:] MDPI [Place:] Basel [Year:] 2015 [Pages:] 474-490
Publisher: 
MDPI, Basel
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.
Subjects: 
hedge fund
alpha stream
alpha weights
portfolio turnover
investment allocation
weighted regression
diversification
bounds
optimization
factor models
JEL: 
G00
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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