An Overview on Mathematical Finance

Abstract

Mathematical finance is a field of applied mathematics which deals with the application of mathematical methods to the solution of problems in finance. In this field, tools of stochastic processes, PDEs, optimisation and control theory are extensively used to model financial processes. One of the goals of mathematical finance is to price financial derivatives such as bonds, options and future contracts in a high accuracy. Another objective is the development of optimal strategies for executing buy and sell orders. The area of mathematical finance have changed the financial markets over the last few decades and lead to the creation of computerised trading algorithms. As a result, significant number of "algo-traiding" companies has emerged. The speaker introduces some of the problems and challenges which are studied in this field and gives an exposure to a few developments that were made over the years.

About the speaker

Dr. Eyal Neuman received his MSc in operations research from the Technion - Israel Institute of Technology in 2010, and got his PhD in operations research from the Technion in 2014 (supervised by Prof Leonid Mytnik). During his MSc and PhD career, he focused on the field of probability and stochastic processes. Mainly he has been working on stochastic partial differential equations and sample paths properties of stochastic processes. In June 2014, he joined IAS of HKUST as a Postdoctoral Fellow. He has authored and co-authored 5 papers, and his current research interests include: (1) Stochastic partial differential equations; (2) Stochastic interacting particle systems; (3) Mathematical finance.

Dr. Neuman works with Prof. ZHENG Xinghua, Department of Information Systems, Business Statistics and Operations Management.