A Bayesian Analysis of Dual Trader Informativeness in Futures Markets

Posted: 27 Aug 2002

See all articles by Kai Li

Kai Li

University of British Columbia (UBC) - Sauder School of Business; China Academy of Financial Research (CAFR)

Sugato Chakravarty

Purdue University

Multiple version iconThere are 2 versions of this paper

Abstract

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

Li, Kai and Chakravarty, Sugato, A Bayesian Analysis of Dual Trader Informativeness in Futures Markets. Forthcoming in Journal of Empirical Finance. Available at SSRN: https://ssrn.com/abstract=326402

Kai Li

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

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada
604-822-8353 (Phone)
604-822-4695 (Fax)

HOME PAGE: http://finance.sauder.ubc.ca/~kaili

China Academy of Financial Research (CAFR)

1954 Huashan Road
Shanghai P.R.China, 200030
China

Sugato Chakravarty (Contact Author)

Purdue University ( email )

Consumer Sciences
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West Lafayette, IN 47906
United States
765-494-6427 (Phone)
765-494-0869 (Fax)

HOME PAGE: http://web.ics.purdue.edu/~sugato

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