We provide an overview of automatic differentiation (AD), a technique for the efficient computation of derivatives of functions defined in some programming language. We give a short explanation of how AD works, indicate the anticipated cost of derivatives computed using AD, and survey what AD...

We study the risk assessment of uncertain cash flows in terms of dynamic convex risk measures for processes as introduced in Cheridito et al. (Electron. J. Probab. 11(3):57–106, 2006). These risk measures take into account not only the amounts but also the timing of a cash flow. We discuss...

Continuous time models in the theory of real options give explicit formulas for optimal exercise strategies when options are simple and the price of an underlying asset follows a geometric Brownian motion. This paper suggests a general, computationally simple approach to real options in discrete...

This paper extends Svensson and Woodford’s (2003) partial information framework by allowing the private agents to achieve robustness against incomplete information about the structure of the economy by distorting their expectations in a particular direction. It shows how a linear rational...

We propose a decomposition method for the solution of a dynamic portfolio optimization problem which fits the formulation of a multistage stochastic programming problem. The method allows to obtain time and nodal decomposition of the problem in its arborescent formulation applying a discrete...