EE Seminar: Challenges in Algorithmic Trading: Machine Learning, Optimal Control and Convex Optimization
(The talk will be given in English)
Speaker: Dr. Doron Blatt
DRW Trading, Chicago
Sunday, April 14th, 2019
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Challenges in Algorithmic Trading: Machine Learning, Optimal Control and Convex Optimization
Abstract
The financial market has evolved in a few short decades from in-person trading in the pits to an estimated 80% of all trading conducted by automated trading systems. This talk will present the key components of the electronic marketplace. The basic building block of electronic trading is the Central Limit Order Book (CLOB), a continuous double auction where supply meets demand and price discovery takes place. I will discuss a model for the CLOB and an optimal control problem that can be formulated and solved to optimize execution strategies. Predicting future prices is the “holy grail” of algorithmic trading. I will give an example where machine learning can be used to make such predictions and discuss the challenges of non-stationary data and “big p little n”. Given predictions, constructing optimal portfolios is an area with many unsolved challenges and research opportunities. The talk will cover other important topics such as preventing over-fitting, online convex optimization and multi-arm bandit problems.
Short Bio
Doron Blatt received his B.Sc. and M.Sc. from Tel Aviv University and Ph.D. from the University of Michigan in Electrical Engineering. He conducted research on signal processing, machine learning, and optimization. Doron joined DRW Trading in 2006 and became a partner in 2011. Today DRW is one of the largest principal trading firms in the world. Over the past 13 years Doron has built and managed DRW’s algorithmic trading group. Doron is returning to Israel to open DRW’s R&D office in Tel Aviv.
