How Your Counterparty Matters: Using Transaction Networks to Explain Returns in CCP Marketplaces
University of Maryland - College Park
Andrei A. Kirilenko
Massachusetts Institute of Technology (MIT) Sloan School of Management
Università di Roma "La Sapienza"; Institute for the Study of Labor (IZA); Einaudi Institute for Economics and Finance (EIEF)
December 1, 2011
We study the profitability of traders in two fully electronic, highly liquid markets, the Dow and S&P 500 e-mini futures markets. We document and seek to explain the fact that traders that transact with each other in this market have highly correlated returns. While traditional least squares regressions explain less than 1% of the variation in trader-level returns, using the network pattern of trades, our regressions explain more than 70% of the variation in returns. Our approach includes a simple representation of how much a shock is amplified by the network and how widely it is transmitted. It provides a possible short-hand for understanding the consequences of a fat-finger trade, a withdrawing of liquidity, or other market shock. In the S&P 500 and DOW futures markets, we find that shocks can be amplified more than 50 times their original size and spread far across the network. We interpret the link between network patterns and returns as reflecting differences in trading strategies. In the absence of direct knowledge of traders' particular strategies, the network pattern of trades captures the relationships between behavior in the market and returns. We exploit these methods to conduct a policy experiment on the impact of trading limits.
Number of Pages in PDF File: 47
Keywords: Financial networks, systemic risk, interconnections, network centrality, spatial autoregressive models, trading limits
JEL Classification: G10, C21working papers series
Date posted: April 30, 2010 ; Last revised: January 31, 2012
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