47 Pages Posted: 30 Apr 2010 Last revised: 31 Jan 2012
Date Written: 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.
Keywords: Financial networks, systemic risk, interconnections, network centrality, spatial autoregressive models, trading limits
JEL Classification: G10, C21
Suggested Citation: Suggested Citation
Cohen-Cole, Ethan and Kirilenko, Andrei A. and Patacchini, Eleonora, How Your Counterparty Matters: Using Transaction Networks to Explain Returns in CCP Marketplaces (December 1, 2011). Available at SSRN: https://ssrn.com/abstract=1597738 or http://dx.doi.org/10.2139/ssrn.1597738