On the Informational Properties of Trading Networks

Trading Networks, 2017, Econometrics Journal 20(3), S126-S149

29 Pages Posted: 17 Mar 2009 Last revised: 6 Aug 2019

See all articles by Lada Adamic

Lada Adamic

University of Michigan at Ann Arbor; Xerox Corp. - Palo Alto Research Center

Celso Brunetti

Board of Governors of the Federal Reserve System

Jeffrey H. Harris

American University - Department of Finance and Real Estate

Andrei A. Kirilenko

University of Cambridge - Finance

Multiple version iconThere are 2 versions of this paper

Date Written: September 9, 2009

Abstract

We apply network analysis to trace patterns of information transmission in an electronic limit order market. If market orders or large executable limit orders are submitted by informed traders, then resulting star-shaped or diamond-shaped patterns – or trading networks – should be associated with large changes in returns, smaller volume, and short duration between trades. In contrast, the execution of small limit orders from uninformed traders should result in networks with many triangular and reciprocal patterns and be associated with smaller changes in returns, larger volume and longer duration between trades. We compute a time series of trading networks using audit trail, transaction-level data for all regular transactions in the September 2008 E-mini S&P 500 futures contract – the cornerstone of price discovery for the S&P 500 Index. We find that network metrics that quantify the shape of a network are statistically significantly related to returns, volatility, volume, and duration.

Keywords: trading networks, financial networks, limit order book, limit order markets

JEL Classification: G12, D82, D83, D85

Suggested Citation

Adamic, Lada and Brunetti, Celso and Harris, Jeffrey H. and Kirilenko, Andrei A., On the Informational Properties of Trading Networks (September 9, 2009). Trading Networks, 2017, Econometrics Journal 20(3), S126-S149. Available at SSRN: https://ssrn.com/abstract=1361184 or http://dx.doi.org/10.2139/ssrn.1361184

Lada Adamic

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States
+1 (734) 615 2132 (Phone)

HOME PAGE: http://www-personal.umich.edu/~ladamic

Xerox Corp. - Palo Alto Research Center ( email )

3333 Coyote Hill Road
Palo Alto, CA 94304-1314
United States
650-812-4147 (Phone)

Celso Brunetti

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Jeffrey H. Harris

American University - Department of Finance and Real Estate ( email )

Kogod School of Business
4400 Massachusetts Ave., N.W.
Washington, DC 20016-8044
United States
202-885-6669 (Phone)

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