Trading networks

IF 2.9 4区经济学 Q1 ECONOMICS

Econometrics Journal Pub Date : 2017-04-05 DOI:10.1111/ectj.12090

Lada Adamic, Celso Brunetti, Jeffrey H. Harris, Andrei Kirilenko

引用次数: 43

Abstract

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.

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交易网络

在本文中，我们分析了E-mini标准普尔500指数期货合约中12000多个交易员网络的时间序列，并将网络变量与更常用来描述市场状况的金融变量联系起来。我们表明，网络变量导致交易量、交易间持续时间、有效价差、贸易失衡和其他市场流动性指标。网络变量反映了信息、信息不对称和市场流动性，并在交易量或流动性措施之前显著地预示了未来的市场状况。我们还发现网络变量与回报和波动之间存在双向格兰杰因果关系，突出了市场条件和交易行为之间的强烈反馈。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Econometrics Journal 管理科学-数学跨学科应用

CiteScore

4.20

自引率

5.30%

发文量

审稿时长

>12 weeks

期刊介绍： The Econometrics Journal was established in 1998 by the Royal Economic Society with the aim of creating a top international field journal for the publication of econometric research with a standard of intellectual rigour and academic standing similar to those of the pre-existing top field journals in econometrics. The Econometrics Journal is committed to publishing first-class papers in macro-, micro- and financial econometrics. It is a general journal for econometric research open to all areas of econometrics, whether applied, computational, methodological or theoretical contributions.