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Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

by Kirilenko, Andrei A. , Lo, Andrew W.

in Algorithms / Arbitrage / Automation / Business orders / Capital market / Commodity futures / Computer science / Computers / Cost control / Dow Jones averages / Economic incentives / Economics / Electronic trading systems / Financial incentives / Financial markets / Financial portfolios / Financial regulation / Financial securities / Futures trading / High frequency trading / Initial public offerings / Innovations / Investment advisors / Investors / Laboratories / Law / Liquidity / Markets / Nasdaq Composite Index / Optimization / Population growth / Portfolios / Program trading / Regulation of financial institutions / Securities trading / Stock exchanges / Studies / Symposium: The Growth of the Financial Sector / Technological change / Technology / Trade volume / Trading / Transaction costs / Transactions / Transformation

2013

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Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

by Kirilenko, Andrei A. , Lo, Andrew W.

2013

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Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

by Kirilenko, Andrei A. , Lo, Andrew W.

2013

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Journal Article

Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

Kirilenko, Andrei A.,

Lo, Andrew W.

2013

Overview

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.

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American Economic Association

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