Using Short-Term Predictions for Participation-Rate Driven Trading Algorithms

20 Pages Posted: 2 Dec 2012 Last revised: 16 Apr 2013

See all articles by Ngoc-Minh Dang

Ngoc-Minh Dang

State Street Global Markets

Charles-Albert Lehalle

Abu Dhabi Investment Authority, ADIA; Imperial College London

Date Written: December 1, 2012

Abstract

We propose a decomposition of algorithm’s a priori performance, from which we sep- arate contributions came from different factors. We show that, in combining estimations on volume and price and always taking into account the price-impact effect, one is able to optimize the execution in a sequential manner, which we refer to as on-line optimization. We illustrate the ability to adapt to real execution context, respect algorithm’s constraint and achieve better performance of the proposed method in the optimal execution problem.

Keywords: optimal liquidation, on-line optimization, VWAP, IS, PVOL, slippage

Suggested Citation

Dang, Ngoc-Minh and Lehalle, Charles-Albert, Using Short-Term Predictions for Participation-Rate Driven Trading Algorithms (December 1, 2012). Available at SSRN: https://ssrn.com/abstract=2183682 or http://dx.doi.org/10.2139/ssrn.2183682

Ngoc-Minh Dang (Contact Author)

State Street Global Markets

Hong Kong
China

Charles-Albert Lehalle

Abu Dhabi Investment Authority, ADIA ( email )

211 Corniche Road
Abu Dhabi
United Arab Emirates

HOME PAGE: http://https://www.adia.ae/

Imperial College London ( email )

South Kensington Campus
Imperial College
LONDON, SW7 2AZ
United Kingdom