Finance and Risk Engineering Faculty Lend their Expertise to Advance the Field

Roy S. Freedman — an adjunct professor in the Department of Finance and Risk Engineering, the author of the highly regarded textbook Introduction to Financial Technology, and the founder of the consulting firm Inductive Solutions — has been appointed to the IEEE Computational Intelligence Society’s Computational Finance and Economics Technical Committee. IEEE (Institute of Electrical and Electronics Engineers), the world's largest association of technical professionals, focuses on the educational and technical advancement of electrical and electronic engineering, telecommunications, computer engineering and allied disciplines.

The scope of the Technical Committee includes the development of advanced computing techniques for financial and economic applications and the application of research in computational methods to real-world financial and economic systems. These systems have become indispensable in virtually all financial applications, from portfolio selection, trading, and risk management to compliance and market regulation. The Committee also coordinates the annual IEEE Symposium on Computational Intelligence for Financial Engineering & Economics (CIFEr), one of the leading international forums for the engineering and financial communities. Freedman is an active figure in the field and chaired the IEEE’s First International Conference on Artificial Intelligence Applications on Wall Street in 1991.

Andrey Itkin, an adjunct professor in the Department of Finance and Risk Engineering, will serve as a managing editor of a special issue of the Journal of Computational Sciences. The journal provides an international platform in which to exchange novel research results in simulation-based science across all scientific disciplines.

The special issue, scheduled to be published in early 2017, will collect topics in computational and algorithmic finance, an area with great practical application, including pricing and hedging of derivatives and the risk management of financial instruments.

Along with fellow editors, Itkin — who also directs quantitative research at Bank of America Merrill Lynch — is currently soliciting research papers on such matters as machine learning and neural networks as they apply to finance; advances in Monte Carlo and quasi- Monte Carlo methodologies, as well as new strategies for market factors simulation; numerical techniques and tools for algorithmic and high-frequency trading; and more.