Available online at www.sciencedirect.com Mathematics and Computers in Simulation 79 (2008) 429–436 The dynamic relations among return volatility, trading imbalance, and trading volume in futures markets An-Sing Chen a,1 , Hung-Gay Fung b,2 , Erin H.C. Kao c,∗ a Department of Finance, National Chung Cheng University, Ming Hsiung, Chia Yi 621, Taiwan, ROC b College of Business Administration, and Center for International Studies, University of Missouri, St. Louis, One University Blvd., St. Louis, MO 63121, United States c Department of Finance, Ling Tung University, Nantun, Taichung 40852, Taiwan, ROC Received 5 January 2008; received in revised form 17 January 2008; accepted 19 January 2008 Available online 13 February 2008 Abstract Trading imbalances reflect the quality of market information and may contain more information than the number of trades or trading volume. In order to better understand how trading imbalances play a role different from traditional variables (i.e., number of trades and trading volume) in explaining volatility, we use intraday data to examine the dynamic relations among return volatility, trading imbalances, and traditional variables for E-mini S&P 500 futures and Japanese Yen futures contracts, respectively. The Granger-causality tests indicate strong feedback effects between volatility and trading variables, confirming the information- based and hedging-based trading. We also compare the results of the traditional volumes and trading imbalances through variance decomposition and impulse responses analysis. It is shown that the sequential arrival of private information through trading imbalance is more important in explaining return volatility than the traditional variables, which are a proxy for the public information. © 2008 IMACS. Published by Elsevier B.V. All rights reserved. Keywords: Trading imbalance; Information-based trading; Hedging-based trading; Granger-causality test; Impulse response analysis 1. Introduction New information releases usually prompt heavy trading and volatility shocks. Many studies, including Clark [2], Tauchen and Pitts [13], Jones et al. [9], Andersen [1], Xu et al. [15], and Ludvigson and Ng [10], have examined the volatility–volume relation that is related to the information-based hypothesis. Since trade occurs at the time of public information releases, the number of trades or the trading volume used in the literature in the analysis of volume–volatility relation can be viewed as a proxy for the public information. In an asymmetric information environment, informed traders conduct trades that are closely related to private information. If more informed traders are confident of the information they possess, their orders will cluster on one side of trading and will cause a greater trading imbalance, thereby inducing a drastic change in asset prices. Trade imbalances reflect the quality of information, which is private, and hence affects the pricing dynamics. That ∗ Corresponding author. Tel.: +886 4 3600 8600. E-mail addresses: finasc@ccu.edu.tw (A.-S. Chen), fungh@msx.umsl.edu (H.-G. Fung), erinkao@mail.ltu.edu.tw (E.H.C. Kao). 1 Tel.: +886 5 2720411x34201; fax: +886 5 2720818. 2 Tel.: +1 314 516 6374; fax: +1 314 516 6420. 0378-4754/$32.00 © 2008 IMACS. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.matcom.2008.01.045