Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/44948 
Erscheinungsjahr: 
2008
Schriftenreihe/Nr.: 
Discussion Papers in Statistics and Econometrics No. 1/08
Verlag: 
University of Cologne, Seminar of Economic and Social Statistics, Cologne
Zusammenfassung: 
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.
Schlagwörter: 
Bayesian portfolio optimization
Gordin's condition
Markov chain Monte Carlo
Stylized facts
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
180.23 kB





Publikationen in EconStor sind urheberrechtlich geschützt.