Would Position Limits Have Made any Difference to the 'Flash Crash' on May 6, 2010

39 Pages Posted: 3 Nov 2010 Last revised: 13 Nov 2013

See all articles by Bernard Lee

Bernard Lee

HedgeSPA (Hedge Funds and Sophisticated Products Advisors)

Shih-Fen Cheng

School of Computing and Information Systems, Singapore Management University

Annie Koh

Singapore Management University; Singapore Management University - Business Development and External Relations

Date Written: November 1, 2010

Abstract

On May 6, 2010, the US equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (DJIA) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. Earlier research by Lee, Cheng and Koh (2010) identified the conditions under which a “flash crash” can be triggered by systematic traders running highly similar trading strategies, especially when they are “crowding out” other liquidity providers in the market. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of “flash crash” observed in their earlier study (2010). While some commentators assigned blame to high-frequency trading, our analysis was unable to identify a direct link to high-frequency trading per se, but rather the domination of market activities by trading strategies that are responding to the same set of market variables in similar ways, as well as various pre-existing market micro-structural safety mechanisms with unintended consequences when triggered simultaneously. The consequent lack of market participants interested in the “other side” of their trades may result in a significant liquidity withdrawal during extreme market movements. This paper describes the results of 9 different simulations created by using a large-scale computer model to reconstruct the critical elements of the market events of May 6, 2010. The resulting price distribution provides a reasonable resemblance to the descriptive statistics of the second-by-second prices of S&P500 e-Mini futures from 14:30 to 15:00 on May 6, 2010. There are no a priori assumptions made on asset price distributions, and our description of market dynamics is purely based on the structure of the market and the key types of market participants involved. This type of simulation avoids “over-fitting” historical data, and can therefore provide regulators with deeper insights on the possible drivers of the “flash crash”, as well as what type of policy responses may work or may not work under comparable market circumstances in the future. Our results also lead to a natural question for policy markers: If certain prescriptive measures such as position limits have a low probability of meeting its policy objectives on a day like May 6, will there be any other more effective counter measures without unintended consequences?

Keywords: 6 May 2010, Flash Crash, Liquidity Withdrawal, Extreme Market Movements, Agent-based Simulation, Speculative Activities, Position Limits

JEL Classification: G13, G15, G18

Suggested Citation

Lee, Bernard and Cheng, Shih-Fen and Koh, Annie and Koh, Annie, Would Position Limits Have Made any Difference to the 'Flash Crash' on May 6, 2010 (November 1, 2010). Available at SSRN: https://ssrn.com/abstract=1701078 or http://dx.doi.org/10.2139/ssrn.1701078

Bernard Lee (Contact Author)

HedgeSPA (Hedge Funds and Sophisticated Products Advisors) ( email )

c/o NUS Enterprise
71 Ayer Rajah Crescent #18-03C
Singapore, 139951
Singapore

HOME PAGE: http://www.hedgespa.com

Shih-Fen Cheng

School of Computing and Information Systems, Singapore Management University ( email )

80 Stamford Road
178902
Singapore

Annie Koh

Singapore Management University ( email )

Administration Building
81 Victoria Street
Singapore, 188065
Singapore

Singapore Management University - Business Development and External Relations ( email )

81 Victoria Street
Admin Bldg, Level 5
Singapore, 188065
Singapore

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
450
Abstract Views
4,721
Rank
117,962
PlumX Metrics