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Title:A general approach to Bayesian portfolio optimization PDF Logo
Authors:Bade, Alexander
Frahm, Gabriel
Jaekel, Uwe
Issue Date:2008
Series/Report no.:Discussion papers in statistics and econometrics 1/08
Abstract:We develop a general approach to portfolio optimization taking account of estimation risk and stylized facts of empirical finance. This is done within a Bayesian framework. The approximation of the posterior distribution of the unknown model parameters is based on a parallel tempering algorithm. The portfolio optimization is done using the first two moments of the predictive discrete asset return distribution. For illustration purposes we apply our method to empirical stock market data where daily asset logreturns are assumed to follow an orthogonal MGARCH process with t-distributed perturbations. Our results are compared with other portfolios suggested by popular optimization strategies.
Subjects:Bayesian portfolio optimization
Gordin's condition
Markov chain Monte Carlo
Stylized facts
Document Type:Working Paper
Appears in Collections:Discussion Papers in Econometrics and Statistics, Institut für Ökonometrie und Statistik, Universität Köln

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