Moore's Law vs. Murphy's Law: Algorithmic Trading and Its Discontents

Journal of Economic Perspectives (2013)

21 Pages Posted: 20 Mar 2013 Last revised: 22 Jul 2017

See all articles by Andrei A. Kirilenko

Andrei A. Kirilenko

Imperial College London - Centre for Global Finance and Technology

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Date Written: March 19, 2013

Abstract

Financial markets have undergone a remarkable transformation over the past two decades due to advances in technology. These advances include faster and cheaper computers, greater connectivity among market participants, and perhaps most important of all, more sophisticated trading algorithms. The benefits of such financial technology are evident: lower transactions costs, faster executions, and greater volume of trades. However, like any technology, trading technology has unintended consequences. In this paper, we review key innovations in trading technology starting with portfolio optimization in the 1950s and ending with high-frequency trading in the late 2000s, as well as opportunities, challenges, and economic incentives that accompanied these developments. We also discuss potential threats to financial stability created or facilitated by algorithmic trading and propose “Financial Regulation 2.0,” a set of design principles for bringing the current financial regulatory framework into the Digital Age.

Keywords: Algorithmic Trading, High Frequency Trading, Financial Regulation, Systemic Risk

JEL Classification: G28, G18, G24, G20

Suggested Citation

Kirilenko, Andrei A. and Lo, Andrew W., Moore's Law vs. Murphy's Law: Algorithmic Trading and Its Discontents (March 19, 2013). Journal of Economic Perspectives (2013). Available at SSRN: https://ssrn.com/abstract=2235963 or http://dx.doi.org/10.2139/ssrn.2235963

Andrei A. Kirilenko

Imperial College London - Centre for Global Finance and Technology ( email )

South Kensington Campus
London, SW7 2AZ
United Kingdom

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

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