Intermediate Mathematics: Understanding Stochastic Calculus

The use of probability theory in financial modelling can be traced back to the work on Bachelier at the beginning of last century with advanced probabilistic methods being introduced for the first time by Black, Scholes and Merton in the seventies. The modern financial quantitative analysts make use of sophisticated mathematical concepts, such as martingales and stochastic integration, in order to describe the behaviour of the markets or to derive computing methods.

Dan Crisan is a Professor in Mathematics at Imperial College London. His expertise is in the area of Stochastic Analysis with applications in Engineering and Finance. He has published over 30 articles in journals world-wide and his current research involves developing high-order numerical algorithms for solving stochastic and deterministic partial differential equations, approximating schemes for backward stochastic differential equations and particle methods for nonlinear filtering.

Audience:

• Quantitative analysts
• Financial engineers
• Researchers
• Risk managers
• Structurers
• Market analysts and product controllers