Estimates of Parameters of a Kyle-Type Model Around Earnings Announcements

45 Pages Posted: 8 Mar 2006

See all articles by Yu Cong

Yu Cong

Towson University

Rani Hoitash

Bentley University - Department of Accountancy

Murugappa (Murgie) Krishnan

Yeshiva University

Date Written: September 2006


Using NYSE TAQ data, we compute MLEs of the primitive parameters of a Kyle-type model, including the variance of fundamentals given only public information, the variance of errors in private signals, and the variance of uninformed liquidity trading (noise). An out of sample test shows that the Kyle-type model we use is a good candidate for describing the setting generating our data.

Given rational behavior, our overall pattern of estimates suggests that earnings announcement windows are not periods with "more" public information but periods with "different" public information. Liquidity noise is higher within an earnings announcement window. The variance of beliefs given only public information is also higher within an earnings announcement window, in line with the Fischer-Stocken (2004) argument that agents with more ability and opportunity to manipulate a disclosure cause the disclosure to be more variable. The variance of private information error is smaller in an event window, consistent with greater information acquisition to try and interpret a public announcement. We also document that Kyle's is higher in an event window, showing an overall increase in information asymmetry. We also find that abnormal trading volume in an event window is driven primarily by a greater diffuseness of beliefs given public information alone, and even more so, liquidity noise, and is not significantly related to acquisition of private information.

Keywords: event study, market microstructure, earnings announcements

JEL Classification: G14, G29, D84, M41, M45

Suggested Citation

Cong, Yu and Hoitash, Rani and Krishnan, Murugappa (Murgie), Estimates of Parameters of a Kyle-Type Model Around Earnings Announcements (September 2006). Available at SSRN: or

Yu Cong

Towson University ( email )

8000 York Road, ST 100A
Towson, MD 21204
United States

Rani Hoitash

Bentley University - Department of Accountancy ( email )

175 Forest Street
Waltham, MA 02452-4705
United States


Murugappa (Murgie) Krishnan (Contact Author)

Yeshiva University ( email )

500 West 185th Street
New York, NY 10033
United States

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