Linear Methods are often used to compute approximate solutions to dynamic models, as these models often cannot be solved analytically. Linear methods are very popular, as they can easily be implemented. Also, they provide a useful starting point for understanding more elaborate numerical...

In this paper we develop several regression algorithms for solving general stochastic optimal control problems via Monte Carlo. This type of algorithms is particularly useful for problems with a highdimensional state space and complex dependence structure of the underlying Markov process with...

This paper relates recursive utility in continuous time to its discrete-time origins and provides a rigorous and intuitive alternative to a heuristic approach presented in [Duffie, Epstein 1992], who formally define recursive utility in continuous time via backward stochastic differential...

Banks should evaluate whether a borrower is likely to default. The author applies several techniques in the extensive mathematical literature of stochastic optimal control/dynamic programming to derive an optimal debt in an environment where there are risks on both the asset and liabilities...

Creditors, banks and bank regulators should evaluate whether a borrower is likely to default. I apply several techniques in the extensive mathematical literature of stochastic optimal control/dynamic programming to derive an optimal debt in an environment where there are risks on both the asset...

A healthy financial system encourages the efficient allocation of capital and risk. The collapse of the house price bubble led to the financial crisis that started in 2007. There is a large empirical literature concerning the relation between asset price bubbles and financial crises. I evaluate...

Alan Greenspan’s paper (March 2010) presents his retrospective view of the crisis. His theme has several parts. First, the housing price bubble, its subsequent collapse and the financial crisis were not predicted either by the market, the FED, the IMF or the regulators in the years leading to...

We investigate financial markets under model risk caused by uncertain volatilities. For this purpose we consider a financial market that features volatility uncertainty. To have a mathematical consistent framework we use the notion of G-expectation and its corresponding G-Brownian motion...

This note extends the finding of Benhabib and Rusticchini (1994) who provide a class of SDGE models, whose solution is characterized by a constant savings rate. We show that this class of models may be interpreted as a standard representative agent SDGE model with costly adjustment of capital...

We study the valuation and hedging of unit-linked life insurance contracts in a setting where mortality intensity is governed by a stochastic process. We focus on model risk arising from different specifications for the mortality intensity. To do so we assume that the mortality intensity is...