A Bayesian Analysis of Dual Trader Informativeness in Futures Markets

26 Pages Posted: 27 Aug 2002

See all articles by Sugato Chakravarty

Sugato Chakravarty

Kai Li

University of British Columbia (UBC) - Sauder School of Business; Asian Bureau of Finance and Economic Research (ABFER); China Academy of Financial Research (CAFR); European Corporate Governance Institute (ECGI); Canadian Sustainable Finance Network (CSFN)

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Date Written: June 2002


We take a closer look at the question of whether dual traders in futures markets are indeed informed traders. Underpinning this question is the intuition that a dual trader's decision to trade on his own account is not random, but is endogenously determined by his expectations of trading profits related to this decision. We employ a simultaneous equations model with two endogenous variables: (1) the binary decision of own account trading (or not), and (2) the trading profit resulting from his own account trading. Our test of whether dual traders are informed traders comprises of estimating the correlation between the error terms of the two equations in our model, where one error term proxies for a dual trader's unobserved private information and the other captures his abnormal profit. Upon estimating the model, using the Bayesian approach, we find no evidence of significant correlation between a dual trader's private information and his abnormal profit. Overall, dual traders appear to be uninformed traders with distinct trade-related characteristics.

Keywords: endogeneity, heterogeneity, informed trader, Markov chain Monte Carlo, private information, simultaneous equations

JEL Classification: G20, G28, C11, C15, C35

Suggested Citation

Chakravarty, Sugato and Li, Kai, A Bayesian Analysis of Dual Trader Informativeness in Futures Markets (June 2002). Sauder School of Business Working Paper, Available at SSRN: https://ssrn.com/abstract=316571 or http://dx.doi.org/10.2139/ssrn.316571

Kai Li

University of British Columbia (UBC) - Sauder School of Business ( email )

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Canadian Sustainable Finance Network (CSFN) ( email )

Queens University
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