Optimal Execution in the Age of Big Data

Irene Aldridge, ABLE Alpha Trading, LTD.

Optimal Execution refers to the science of executing an order in today's fragmented electronic markets. While many brokers and other market participants still insist on executing orders using intuition and by manually timing the markets, researchers in financial mathematics have developed fine techniques for quick identification of optimal trading conditions. And the industry is taking notice -- in the Optimal Execution course I teach for executives from all spectrum of investment lifecycle, nearly 50% of my students routinely come from the largest hedge funds in the U.S. These hedge funds are dissatisfied with the level of sophistication exhibited by their brokers and they are quietly building their own departments with proprietary execution strategies based on the latest cutting-edge research.

Some of this research will be on display at the upcoming Big Data Finance 2014 conference to be held at New York University's Courant Institute for Mathematical Sciences on February 14 from 1 PM to 6 PM.

The event will feature stars in the field of high-frequency execution such as Steve Shreve of Carnegie Mellon and Marco Avellaneda of Courant Institute of NYU.

The latest research that Prof. Avellaneda is confirmed to present is nothing short of fascinating. Imagine yourself as a portfolio manager that has detected an abrupt change in market conditions, and needs to SELL, SELL, SELL right away. Furthermore, imagine that the position you need to liquidate is close to a billion dollars, and you still want to obtain a reasonable price and avoid causing another flash crash (unlike some portfolio managers unwinding their positions on May 6, 2010). What do you do?

Well, according to the model of Prof. Avellaneda, you can instead sell other strategically-chosen financial instruments in specific quantities to gain liquidity. Then, once the relevant risk parameters of your portfolio are in place, you can gradually adjust your position to achieve the desired mix of instruments in your portfolio. At the Big Data Finance conference, Prof. Avellaneda will present his brand-new research for the very first time.

Other topics discussed at the conference will include:

• Managing reams of financial data in derivatives, a perspective of Morgan Stanley and major hedge funds
• Short-term order book repopulation dynamics that can be used to fine-tune intraday execution.
• The cost of latency and other leading edge topics in finance.

Don't miss this exciting opportunity to update your toolkit and to network with like-minded colleagues. Here is the link to the full conference website.

About The Author: Irene Aldridge is a Managing Partner at ABLE Alpha Trading, LTD., a high-frequency and quant investment consultancy. Ms. Aldridge is the author of High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems (Wiley), translated into Chinese and now in its second edition. She can be reached at [email protected].