A C{0,1}-functional Ito formula and its applications in finance.

Speaker: Xiaolu Tan from Chinese University of Hong Kong Date and Time: 9/10/2020 at 9:00 AM Zoom:  992 7853 8762 Abstract:  We obtain a functional (path-dependent) extension of the Ito formula for C{0,1}-functions in Bandini and Russo (2017). We then provide some original applications in finance of this new formula, by considering an option replication […]

REU 2020 Cancelled due to Pandemic

Due to the coronavirus (covid-19) outbreak, we will not be able to host the CIMS REU in Industrial Mathematics and Statistics in Summer 2020.  We thank you for your applications, as we got to learn about all of your efforts in mathematics and science, and are disappointed that our program cannot go forward this year.  […]

Impulse Control Problems: Solution and Modeling

Speaker: Chao Zhu from University of Wisconsin-Milwaukee Date and Time: 03/16/20, 4-5pm Room: SH306 Abstract: This talk starts with an optimal inventory control problem using a long-term average criterion. In absence of ordering, the inventory process is modeled by a one-dimensional diffusion on some interval of  (-∞, ∞) with general drift and diffusion coefficients and boundary points that are […]

Optimal Investments with Anticipative Information

Speaker: Mauricio Enrique Elizalde Mejía from Universidad Autónoma de Madrid Date and Time: 04/06/2020 Room: SH306 Abstract: We consider the case in which a trader has anticipative information about the value of a stock assumed to be driven by a Brownian motion. We show the usage of two different ways to model the problem; the first […]

Prof. Suzanne Weekes receives Deborah and Franklin Tepper Haimo Award

Suzanne L. Weekes, professor in the mathematical sciences department at Worcester Polytechnic Institute (WPI), has received the prestigious Deborah and Franklin Tepper Haimo Award for Distinguished College or University Teaching of Mathematics from the Mathematical Association of America. More information can be found at

WPI Researcher Uses Math to Help Army Protect Soldiers from Chemical Attack

A nice article on CIMS Member Randy Paffenroth’s work with the U.S. Army Combat Capabilities Development Command Soldier Center (CCDC-SC) on using mathematics and data science for threat analysis in chemical warfare:

Graphon Mean Field Games: A Dynamical Equilibrium Theory for a Networked World

Speaker: Peter Caines from McGill University Date and Time: 03/06/20, 11am-12 Room: SH203 Abstract: The complexity of large population multi-agent dynamical systems, such as occur in economics, communication systems, and environmental and transportation systems, makes centralized control infeasible and classical game theoretic solutions intractable. In this talk we first present the Mean Field Game (MFG) theory of large population […]

Dynamic Noisy Rational Expectations Equilibrium with Heterogeneous Information.

Speaker: Scott Robertson from Boston University Date and Time: 02/24/20, 4-5pm Room: SH306 Abstract: In this talk, we consider equilibria in the presence of asymmetric information and misinformed agents (noise traders). We establish existence of two equilibria. First, a full communication one where the informed agents’ signal is disclosed to the market, and static policies are optimal. […]

Dynamic Index Tracking and Risk Exposure Control Using Derivatives

Speaker: Tim Leung from UW-Seattle Date and Time: 03/23/2020,  4-5pm Abstract: A common challenge faced by many institutional and retail investors is to effectively control risk exposure to various market factors. There is a great variety of indices designed to provide different types of exposures across sectors and asset classes. Some of these indices can be difficult […]

Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization

Speaker: Lingjiong Zhu from Florida State University Date and Time: 11/05/2019,  4-5pm Abstract: Stochastic gradient Hamiltonian Monte Carlo (SGHMC) is a variant of stochastic gradient with momentum where a controlled and properly scaled Gaussian noise is added to the stochastic gradients to steer the iterates towards a global minimum. Many works reported its empirical success […]

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