This paper establishes a general analytical framework for continuous-time stochastic control problems for an ambiguity-averse agent (AAA) with time-inconsistent preference, where the control problems do not satisfy Bellman's principle of optimality. The AAA is concerned about model uncertainty...

In an incomplete market we study the optimal consumption-portfolio decision of an investor with recursive preferences of Epstein-Zin type. Applying a classical dynamic programming approach, we formulate the associated Hamilton-Jacobi-Bellman equation and provide a suitable verification theorem....

A problem of optimally purchasing electricity at a real-valued spot price (that is, with potentially negative cost) has been recently addressed in De Angelis, Ferrari and Moriarty (2015) [SIAM J. Control Optim. 53(3)]. This problem can be considered one of irreversible investment with a cost...

This paper, using the different alternative methods of dynamic optimization (the Lagrange/Kuhn-Tucker (LKT) method, the substitution method, the Hamiltonian method, and the dynamic programming approach) derives the conditions that must be satisfied by the solution to the so-called Ramsey...

We propose two modifications to the method of endogenous grid points that greatly decreases the computational time for life cycle models with many exogenous state variables. First, we use simulated stochastic grids on the exogenous state variables. Second, when we interpolate to find the...

This paper considers an alternative way of structuring stochastic variables in a dynamic programming framework where the model structure dictates that numerical methods of solution are necessary. Rather than estimating integrals within a Bellman equation using quadrature nodes, we use nodes...

One attractive objective for a pensioner using the income drawdown option is to minimise the deviation of the pension fund from a prescribed deterministic target. Typically, this problem is formulated as a linear-quadratic optimal control problem, which has the shortcoming that over-performance...

Economists who want to numerically approximate an elaborate dynamic stochastic programming problem (DSPP), either for structural estimation or policy evaluation purposes, are often confined by the curse of dimensionality: richer models with various state and control variables cannot be solved on...

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using stochastic programming we characterize analytically (rather than numerically) the optimal decisions that follow from characteristic single-stage and multi-stage versions of such...

This chapter gives an overview of current research in evolutionary finance. We mainly focus on the survival and stability properties of investment strategies associated with the Kelly rule. Our approach to the study of the wealth dynamics of investment strategies is inspired by Darwinian ideas...