Imperial College London


Business School

Senior Research Fellow



+44 (0)20 7594 9089a.kirilenko




4.0852-53 Prince's GateSouth Kensington Campus





Andrei Kirilenko is the Director of the Centre for Global Finance and Technology at the Imperial College Business School.

Prior to joining Imperial in August 2015, he was Professor of the Practice of Finance at the MIT Sloan School of Management and Co-Director of the MIT Center for Finance and Policy. Professor Kirilenko's work focuses on the intersection of finance, technology and regulation. He is a recognized world expert on technology in markets, including algorithmic and high frequency trading. He is also an intellectual leader on the principles of regulation of automated financial markets.

Before MIT Sloan, Professor Kirilenko served as Chief Economist of the U.S. Commodity Futures Trading Commission (CFTC) between December 2010 and December 2012. In his capacity as Chief Economist, Kirilenko has been instrumental in using modern analytical tools and methods to improve the Commission's ability to develop and enforce an effective regulatory regime in automated financial markets. In 2010, Kirilenko was the recipient of the CFTC Chairman's Award for Excellence (highest honor). 

Prior to joining the CFTC, Kirilenko spent twelve years at the International Monetary Fund working on global capital markets issues. His scholarly work has appeared in a number of peer-refereed journals and received multiple best-paper awards.  Kirilenko received his PhD in Economics from the University of Pennsylvania, where he specialized in Finance.


The Flash Crash: High Frequency Trading in an Electronic Market (with Albert Kyle, Tugkan Tuzun, and Mehrdad Samadi), 2017, forthcoming in the Journal of Finance.

Trading Networks (with Lada Adamic, Celso Brunetti, and Jeffrey Harris), 2017, forthcoming in the Econometrics Journal.

Genetic Programming Optimization for a Sentiment Feedback Strength-based Trading Strategy (with Steve Y. Yang, Sheung Yin Kevin Mo, and Anqi Liu), 2016, forthcoming in Neurocomputing.

Risk Convection in Commodity Futures Markets (with Ing-Haw Cheng and Wei Xiong), 2015, Review of Finance 19 (5), 1733-1781.

Gaussian Process-Based Algorithmic Trading Strategy Identification (with Steve Yang, Qifeng Qiao, Peter Beling, and William Scherer), 2015, Quantitative Finance.

How Sharing Information Can Garble Experts’ Advice (with Matthew Elliott and Benjamin Golub), 2014, American Economic Review: Papers & Proceedings 104 (5), 463-468.

Trading Networks and Liquidity Provision (with Ethan Cohen-Cole and Eleonora Patacchini), 2014, Journal of Financial Economics 113 (2), 235-251.

Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents (with Andrew W. Lo), 2013, Journal of Economic Perspectives 27 (2), 51-72.

A Multi-Scale Model of High Frequency Trading (with Carmen Meng and Richard Sowers), 2013, Algorithmic Finance 2 (1), 59-98.

Discovering the Ecosystem of an Electronic Financial Market with a Dynamic Machine-Learning Method (with Shawn Mankad and George Michailidis), 2013, Algorithmic Finance 2(2), 151-165.

"Behavior-Based Learning in Identifying High Frequency Trading Strategies" (with Steve Yang, Mark Paddrik, Roy Lee Hayes, Andrew Todd, Peter Beling and William Scherer), 2012, IEEE Computational Intelligence in Financial Engineering and Economics.

Securities Transaction Taxes and Financial Markets (with Karl Habermeier), 2003, IMF Staff Papers, Vol. 50, 165-180.

Valuation and Control in Venture Finance, 2001, Journal of Finance 56 (2), 565-587.

On the Endogeneity of Trading Arrangements, 2000, Journal of Financial Markets 3, 287-31.

Selected Publications

Journal Articles

Adamic L, Brunetti C, Harris JH, et al., 2017, Trading networks, Econometrics Journal, ISSN:1368-4221

KIRILENKO ANDREI, KYLE ALBERTS, SAMADI MEHRDAD, et al., 2017, The Flash Crash: High-Frequency Trading in an Electronic Market, Journal of Finance, Vol:72, ISSN:0022-1082, Pages:967-998


Kirilenko AA, Lo AW, Kirilenko AA, et al., 2013, Moore's law versus Murphy's law: Algorithmic trading and its discontents, Pages:51-72, ISSN:0895-3309

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