Mathematical Finance & Financial Data Science Seminar

Given a set of fully and partially filled equity orders to be used in Transaction Cost Analysis (TCA) a common problem for practitioners is how to correctly account for unfilled shares.   In this talk we first compare and contrast some of the common approaches used in practice today.  Then we show how to formulate the problem in terms of stochastic control.  Finally, by combining classical ideas from the control literature with modern machine learning methods we show how such problems can be efficiently solved numerically.

 

This is joint work with Petter Kolm (NYU Courant) and Dieter Hendricks (RMB).

 

Nick is currently a researcher at the Courant Institute of Mathematical Sciences at NYU working on problems in Stochastic Control and Reinforcement Learning.  Previously he was a Senior Quant Researcher in the Equity Execution group at Citadel focusing on block trading and market Impact.   Prior to that he was at Deutsche Bank involved in the Central Risk Book and Algorithmic Trading.  He holds a PhD from Imperial College London and was a Postdoctoral Research fellow at Humboldt Universitaet Berlin.