Trading networks

被引：25

作者：

Adamic, Lada ^{[1
]}

Brunetti, Celso ^{[2
]}

Harris, Jeffrey H. ^{[3
]}

Kirilenko, Andrei ^{[4
]}

机构：

[1] Univ Michigan, Sch Informat, Ctr Study Complex Syst, Ann Arbor, MI 48109 USA

[2] Fed Reserve Board, Div Res & Stat, Washington, DC USA

[3] Amer Univ, Kogod Sch Business, Washington, DC 20016 USA

[4] Imperial Coll, Ctr Global Finance & Technol, London, England

来源：

ECONOMETRICS JOURNAL | 2017年 / 20卷 / 03期

关键词：

Financial forecasting and simulation; Network formation and analysis; Trading volume; BID-ASK SPREAD; HIGH-FREQUENCY DATA; LIMIT ORDER BOOK; MICROSTRUCTURE NOISE; TRANSACTION PRICES; SECURITIES MARKETS; RETURN VOLATILITY; INFORMED TRADERS; SOCIAL NETWORKS; VARIANCE;

D O I：

10.1111/ectj.12090

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

In this paper, we analyse the time series of 12,000+ networks of traders in the E-mini S&P 500 stock index futures contract and we empirically link network variables with financial variables more commonly used to describe market conditions. We show that network variables lead trading volume, intertrade duration, effective spreads, trade imbalances and other market liquidity measures. Network variables reflect information, information asymmetry and market liquidity and significantly presage future market conditions prior to volume or liquidity measures. We also find two-way Granger-causality between network variables and both returns and volatility, highlighting strong feedback between market conditions and trading behaviour.

引用

页码：S126 / S149

页数：24

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