Combining Alphas via Bounded Regression
Risks 3(4) (2015) 474-490
20 Pages Posted: 17 Jan 2015 Last revised: 5 Nov 2015
Date Written: October 22, 2015
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
JEL Classification: G00
Suggested Citation: Suggested Citation