Inferring Public and Private Information from Trades and Quotes

Posted: 10 Nov 2005

See all articles by Bart Frijns

Bart Frijns

Auckland University of Technology - Faculty of Business & Law

Multiple version iconThere are 2 versions of this paper

Abstract

We propose a new model that uses non-synchronous, ultra-high frequency data to analyze the sequential impact of trades and quotes on the price process. Private information is related to the impact of trades and public information to the impact of quotes. The model is extended to include various other factors that affect public and private information. For 20 active Nasdaq stocks, private information causes, on average, 9.43% of daily stock price movements. Additionally, quotes are more informative when (1) many dealers set the best price and (2) traditional market makers rather than ECNs set the best price.

Keywords: public versus private information, ultra-high frequency data, Nasdaq, market microstructure

JEL Classification: C32, G15

Suggested Citation

Frijns, Bart, Inferring Public and Private Information from Trades and Quotes. Financial Review, Vol. 41, No. 1, February 2006. Available at SSRN: https://ssrn.com/abstract=840167

Bart Frijns (Contact Author)

Auckland University of Technology - Faculty of Business & Law ( email )

3 Wakefield Street
Private Bag 92006
Auckland Central 1020
New Zealand

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