Master Class: Stochastic Control with Applications to Algorithmic Trading 2012-04-12T13:54:04+00:00

The Baruch MFE Program is pleased to offer a one-day Master Class on Stochastic Control with Applications to Algorithmic Trading taught by Dr. Nicholas Westray of Deutsche Bank, on Saturday, April 2.

Seating is limited to 60 participants. Registration for the Master Class is now closed.

This Master Class will provide attendees with a practically oriented overview of stochastic control and will present the latest applications of stochastic control to algorithmic trading.

Synopsis of topics

  • The basic theory of stochastic control
  • The linear quadratic regulator problem
  • Utility maximization and the Merton problem
  • A guide to the stochastic control literature

Applications

  • VWAP trading by optimally following the volume curve
  • How to optimally allocate quantity between a dark pool and a lit venue

 

Program: The detailed program of the Master Class on Stochastic Control with Applications to Algorithmic Trading can be found here.

Audience

Quantitatively oriented finance professionals, academics and students interested in gaining an intuitive and high level introduction to the theory of stochastic control, an area of mathematics with applications as diverse as rocket guidance and inventory management.

Attendees will deepen their knowledge of stochastic control theory and, through practical examples, will see how they can apply the techniques learned to tackle key problems in modern algorithm development/refinement.

Instructor

Nick Westray is a Global Markets quantitative analyst at Deutsche Bank AG in London working on market impact and market microstructure. He is concurrently an honorary research fellow of Imperial College in London, and has a PhD from Imperial College. Nick’s papers appeared in journals such as Finance and Stochastics and Stochastic Processes and their Applications.

Nick was previously a member of the Deutsche Bank Quantitative Products Laboratory in Berlin, where he both performed research and supervised students in the areas of stochastic control applied to curve tracking in illiquid markets and utility maximization using BSDE (Backward Stochastic Differential Equations) methods. Simultaneously, he was closely involved with several projects on the business side within Deutsche Bank, including sector rotation using sparse regression methods and the development of a tool for the calibration and assessment of market impact models. In his dissertation, Nick worked on duality methods in stochastic control and their application to nonsmooth utility maximization.

Schedule

Saturday, April 2

9:00-9:30am Registration

9:30am-12:30pm Morning Session

12:30-2:00pm Lunch Break

2:00-5:00pm Afternoon Session

Location: 55 Lexington Avenue (at 24th Street), Room 3-160, Newman Vertical Campus, Baruch College

Registration:

Practitioner: $550

Student/Academic: $250

Registration for this event is now closed.

Contact

For more information, send email to baruch.mfe@baruch.cuny.edu