This paper describes different GARCH type portfolio models using a bivariate Markov process. In particular we approximate the GARCH process with a Markov chain in order to value the price/return distribution at the investor’s temporal horizon. Then we discuss the computational complexity of the optimization problem and we implement an heuristic algorithm for the global optimum. Finally we propose an ex-post comparison among portfolio selection strategies based on reward/risk performance ratios.
GARCH type portfolio selection models with the Markovian approach
IAQUINTA, Gaetano;ORTOBELLI LOZZA, Sergio;ANGELELLI, Enrico
2011-01-01
Abstract
This paper describes different GARCH type portfolio models using a bivariate Markov process. In particular we approximate the GARCH process with a Markov chain in order to value the price/return distribution at the investor’s temporal horizon. Then we discuss the computational complexity of the optimization problem and we implement an heuristic algorithm for the global optimum. Finally we propose an ex-post comparison among portfolio selection strategies based on reward/risk performance ratios.File allegato/i alla scheda:
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