2 results for Azzato, Jeffrey

  • InfSOCSol2: an Updated MATLAB (R) Package For Approximating the Solution to a Continuous-Time Infinite Horizon Stochastic Optimal Control Problem

    Azzato, Jeffrey; Krawczyk, Jacek B (2008)

    Scholarly text
    Victoria University of Wellington

    This paper describes a suite of MATLAB (R) routines devised to provide an approximately optimal solution to an infinite-horizon stochastic optimal control problem. The suite is an updated version of that described in [Kra01b]. Its routines implement a policy improvement algorithm to optimise a Markov decision chain approximating the original control problem, as described in [Kra01c]

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  • On loss-avoiding lump-sum pension optimization with contingent targets

    Azzato, Jeffrey; Krawczyk, Jacek B; Sissons, Christopher (2011)

    Scholarly text
    Victoria University of Wellington

    Consider a lump-sum pension fund problem, in which an agent deposits an amount with a fund manager up front and is later repaid a lump sum x(T) after time T. The fund manager may be both cautious in seeking a payoff x(T) meeting a certain target, but relaxed toward the possibility of exceeding this target. We use a computational method in stochastic optimal control (“SOCSol”) to find approximately-optimal decision rules for such “cautious-relaxed” fund managers. In particular, we examine fund optimisation problems in which the target is contingent upon market conditions such as inflation.

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