Financial risk management concerns the assessment and identification of risks that originate from the uncertainty of future events in financial markets. These risks need to be quantified and monitored.
The financial crisis has given rise to a reconsideration of some fundamental assumptions that have been standard in mathematical models for the valuation of financial and insurance products regarding risk management. New risk measures that are prescribed by the financial regulator and are currently implemented by the industry are based on mathematics and computations. These measures need to remain effective under circumstances of stress and crisis in financial markets.
Our research group Scientific Computing develops models and methods at the intersection of numerical mathematics and applied probability. Examples are efficient computational methods for quantiles, expectations and variances. Value-at-risk (VaR) and expected shortfall (ES) are standard measures in finance; we also develop risk measures beyond the VaR. Algorithms for so-called backward stochastic differential equations (BSDEs), and dynamic optimization of financial portfolios are developed based on newly developed Monte Carlo methods and Fourier techniques. These methods have applicability in reducing risk in the finance and insurance sectors.
Our research in this area is focused on the development of mathematical models and numerical-solution techniques in the domain of financial and insurance risk management.
Contact person: Kees Oosterlee
Research group: Scientific Computing (SC)
Research partners: Delft University of Technology, Rabobank, ING Bank, VorTech Computing, EY