A Markovian Approximated Solution To A Portfolio Management Problem
AbstractA portfolio management problem is approximated through a Markov decision chain. The weak Euler scheme is applied to discretise the time evolution of a portfolio and an inverse distance method is used to describe the transition probabilities. The approximating Markov decision problem is solved by value iteration. Numerical solutions of varying degrees of accuracy to a few specific portfolio problems are obtained.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 233.
Date of creation: 05 Jul 2000
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Postal: CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain
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- John Rust, 1997. "A Comparison of Policy Iteration Methods for Solving Continuous-State, Infinite-Horizon Markovian Decision Problems Using Random, Quasi-random, and Deterministic Discretizations," Computational Economics 9704001, EconWPA.
- Alistair Windsor & Jacek B. Krawczyk, 1997. "A Matlab Package for Approximating the Solution to a Continuous- Time Stochastic Optimal Control Problem," Computational Economics 9710002, EconWPA.
- Jacek B. Krawczyk & Alistair Windsor, 1997. "An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains," Computational Economics 9710001, EconWPA.
- Foster, Jarred & Krawczyk, Jacek B, 2013. "Sensitivity of cautious-relaxed investment policies to target variation," Working Paper Series 2972, Victoria University of Wellington, School of Economics and Finance.
- Azzato, Jeffrey D. & Krawczyk, Jacek, 2007. "Using a finite horizon numerical optimisation method for a periodic optimal control problem," MPRA Paper 2298, University Library of Munich, Germany.
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