SHERP

Buy-Sell Dependence and Classification Error in Market Microstructure Time-Series Models : A Markov Switching Regression Approach

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Authors
Choe, Hyuk
Issue Date
1999-12
Publisher
College of Business Administration (경영대학)
Citation
Seoul Journal of Business Vol5(1): 89~120(1999)
Keywords
three-state markov chain; time-series data; bid-ask test
Abstract
This paper conducts an empirical test of a market microstructure
model using a new econometric approach. I treat the direction of a trade
as a discrete latent variable following a stationary Markov chain. By
overlaying a three-state Markov chain on a familiar market
microstructure model, I can extract information on the directions of
trades efficiently from time-series data. An analysis of 100 large and
100 small firms for the year 1990 yields several important results: (1)
Order types (sale, cross, purchase) are serially correlated, and the mean
transition probability matrix is very similar for large and small firms. (2)
Information asymmetry is greater for smaller firms. (3) The per share
order processing cost is greater for larger firms. (4) When trades are
classified by the bid-ask test supplemented by the tick test, the
estimated misclassification probabilities are typically small for sales
and purchases, but they are often fairly large for crosses. (5) Buy-sell
classification error results in systematic biases for regression
coefficients.
ISSN
1226-9816
Language
English
URI
http://hdl.handle.net/10371/1645
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College of Business Administration/Business School (경영대학/대학원)Dept. of Business Administration (경영학과)Seoul Journal of BusinessSeoul Journal of Business Volume 05, Number 1/2 (1999)
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