Bayesian Nonparametric Measurement of Factor Betas and Clustering with Application to Hedge Fund Returns

Bayesian Nonparametric Measurement of Factor Betas and Clustering with Application to Hedge Fund Returns

We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return) and betas (to a choice set of explanatory factors) in a multivariate setting. This approach,...

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Bibliographic Details
Main Authors: Urbi Garay, Enrique ter Horst, German Molina, Abel Rodriguez
Format: Article
Language:English
Published: MDPI AG 2016-03-01
Series:Econometrics
Subjects:
nonparametric clustering
Bayesian
cluster
nonparametric alpha and beta
hedge fund performance
Online Access:http://www.mdpi.com/2225-1146/4/1/13

Internet

http://www.mdpi.com/2225-1146/4/1/13

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