We provide an approximation scheme for the maximal expected utility and optimal investment policies for the portfolio choice problem in an incomplete market. Incompleteness stems from the presence of a stochastic factor which affects the dynamics of the correlated stock price. The scheme is built on the Trotter-Kato approximation and is based on an intuitively pleasing splitting of the Hamilton...

Abstract Policy iteration is a widely used technique to solve the Hamilton Jacobi Bellman (HJB) equation, which arises from nonlinear optimal feedback control theory. Its convergence analysis has attracted much attention in unconstrained case. Here we analyze case with constraints both for HJB equations arise deterministic and stochastic cases. The linear each step are solved by an implicit upw...

An optimal finite-time horizon feedback control problem for (semi-linear) wave equations is presented. The feedback law can be derived from the dynamic programming principle and requires to solve the evolutionary Hamilton-Jacobi-Bellman (HJB) equation. Classical discretization methods based on finite elements lead to approximated problems governed by ODEs in high dimensional spaces which makes ...

The valuation of a gas storage facility is characterized as a stochastic control problem, resulting in a Hamilton-Jacobi-Bellman (HJB) equation. In this paper, we present a semi-Lagrangian method for solving the HJB equation for a typical gas storage valuation problem. The method is able to handle a wide class of spot price models that exhibit mean-reverting, seasonality dynamics and price jump...

We study the stochastic Hamilton–Jacobi–Bellman (HJB) equation with jump, which arises from a non-Markovian optimal control problem recursive utility cost functional. The solution to is predictable triplet of random fields. show that value function problem, under some regularity assumptions, HJB equation; and classical this characterizes control. With additional assumptions on coefficients, an ...

We study a class of optimal control problems with state constraints where the state equation is a differential equation with delays. This class includes some problems arising in economics, in particular the so-called models with time to build, see [1, 2, 25]. We embed the problem in a suitable Hilbert space H and consider the associated Hamilton-Jacobi-Bellman (HJB) equation. This kind of infin...

In this paper, we consider a joint dynamic pricing and production policy for stochastic inventory system with perishable products. The demand is dependent on the price level of on-hand inventory. Combined control, optimization model that maximizes total discounted profit built. Applying optimal control theory, formulate problem finding schedule as solving Hamilton-Jacobi-Bellman (HJB) equation....

We investigate a continuous-time mean–variance portfolio selection problem. Different from the general stochastic dynamic programming approach, such as using Hamilton–Jacobi–Bellman (HJB) equation, this paper adopts the Lagrange duality method and the finite difference approach to derive explicit closed-form expressions for the efficient investment strategy and the mean–variance efficient front...

We study a class of optimal control problems with state constraints, where the state equation is a differential equation with delays. This class includes some problems arising in economics, in particular the so-called models with time to build, see [1, 2, 26]. We embed the problem in a suitable Hilbert space H and consider the associated Hamilton-Jacobi-Bellman (HJB) equation. This kind of infi...

Inthispaper,wesolveHamilton-Jocobi-Bellman(HJB)equationsarisinginoptimalcontrolproblems usingHomotopyPerturbationTransformMethod(HPTM).Theproposedmethodisacombinedform oftheLaplaceTransformationMethodwiththeHomotopyPerturbationMethodtoproduceahighly effectivemethodtohandlemanyproblems. ApplyingtheHPTM,solutionprocedurebecomeseasier, simplerandmorestraightforward. Someillustrativeexamplesaregive...