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The Stochastic Programming Extension of the Markowitz Approach

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abstract The stochastic programming methodology applied to the Markowitz approach yields a multistage mean-variance model. The structural properties of the efficient portfolios and the efficient frontiers are derived taking into consideration stochastic dynamic evolvements of the variance-covariance matrices and expected rates of returns over a finite, discrete planning horizon. An aggregation principle is introduced which allows for solving a deterministic convex quadratic single period equivalence program.
   
type conference paper (English)
   
keywords
   
name of conference PASE'95 5th International Workshop on Parallel Applications in Statistics and Economics: Non-Linear Data Analysis (Trier/Mainz, DE)
date of conference 29-8-1995
title of proceedings Neural Network World - International Journal on Neural and Mass-Parallel computing and Information Systems
page(s) 449-460
publisher Institute of Information and Computer Technology ASCR; Faculty of Transport, Czech Polytechnic University, Prague (Prag, CZ)
ISSN 1210-0552
review not reviewed
   
citation Frauendorfer, K. (1995). The Stochastic Programming Extension of the Markowitz Approach. In Neural Network World - International Journal on Neural and Mass-Parallel computing and Information Systems, pp.449-460. Prag, CZ: Institute of Information and Computer Technology ASCR; Faculty of Transport, Czech Polytechnic University, Prague.