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A Markovian Approximated Solution To A Portfolio Management Problem

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  • Jacek B. Krawczyk

    (Victoria University of Wellington)

Abstract

A 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.

Suggested Citation

  • Jacek B. Krawczyk, 2000. "A Markovian Approximated Solution To A Portfolio Management Problem," Computing in Economics and Finance 2000 233, Society for Computational Economics.
    • Handle: RePEc:sce:scecf0:233
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    References listed on IDEAS

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    1. Alistair Windsor & Jacek B. Krawczyk, 1997. "A Matlab Package for Approximating the Solution to a Continuous- Time Stochastic Optimal Control Problem," Computational Economics 9710002, University Library of Munich, Germany.
    2. 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, University Library of Munich, Germany.
    3. Sarkar, Sudipto, 2000. "On the investment-uncertainty relationship in a real options model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(2), pages 219-225, February.
    4. Jacek B. Krawczyk & Alistair Windsor, 1997. "An Approximated Solution to Continuous-Time Stochastic Optimal Control Problems Through Markov Decision Chains," Computational Economics 9710001, University Library of Munich, Germany.
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    Cited by:

    1. Jacek B Krawczyk, 2015. "Delivering Left-Skewed Portfolio Payoff Distributions in the Presence of Transaction Costs," Risks, MDPI, vol. 3(3), pages 1-20, August.
    2. 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.
    3. Behzad Kafash, 2019. "Approximating the Solution of Stochastic Optimal Control Problems and the Merton’s Portfolio Selection Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 763-782, August.
    4. Krawczyk, Jacek B & Pharo, Alastair S, 2014. "InfsocSol3: An updated MATLAB® package for approximating the solution to a continuous-time infinite horizon stochastic optimal control problem," Working Paper Series 3412, Victoria University of Wellington, School of Economics and Finance.
    5. 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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