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Erscheinungsjahr: 
2015
Quellenangabe: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 3 [Issue:] 4 [Publisher:] MDPI [Place:] Basel [Year:] 2015 [Pages:] 474-490
Verlag: 
MDPI, Basel
Zusammenfassung: 
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.
Schlagwörter: 
hedge fund
alpha stream
alpha weights
portfolio turnover
investment allocation
weighted regression
diversification
bounds
optimization
factor models
JEL: 
G00
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