This project focuses both on methodological and applied aspects of financial engineering. The goal is to develop new and original methods to value complex financial products, manage financial risks, and evaluate investment opportunities. The project will focus on the following problems: developing stochastic models to describe dynamics of asset prices and financial variables; developing new, powerful, analytical and computational tools to value complex derivative instruments (path-dependent and multi-variable contracts in particular) and manage risks of derivatives transactions; the eigenfunction expansion approach to derivatives pricing; investigating the issue of model risk in financial engineering; financial engineering for the energy industry; stochastic optimization methodologies in financial engineering, including investment portfolio management under transaction costs and taxes, and dynamic asset/liability management; and real options applications in manufacturing and service industries. To address the national need for advanced training of specialists in financial engineering, the educational component of the project proposes to develop a comprehensive financial engineering curriculum at Northwestern, from the beginning undergraduate to the doctoral level, and create a new Ph.D. major in financial engineering as a part of the IEMS Ph.D. program at Northwestern.
The discipline of financial engineering includes applications of mathematical and statistical modeling and computational technology to problems in the financial services industry and financial management of non-financial corporations and public institutions. This project outlines a broad research program for the next three years. Additionally, it outlines a curriculum development effort, including a new Ph.D. major in financial engineering. This project will support the new Ph.D. program. This project is a part of a long-term development effort at Northwestern in the area of financial engineering. Modeling methodologies, analytical results, and computational algorithms developed in this project will help financial institutions, corporate treasuries, and energy companies accurately value derivative securities, assess model risk, manage investment portfolios, manage assets and liabilities, and apply real options technology to the valuation of businesses and strategic managerial decisions. The education and curriculum development efforts will result in training of highly qualified personnel to enhance competitiveness of the U.S. financial services industry.
