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Activity Number: 425
Type: Contributed
Date/Time: Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
Sponsor: Business and Economics Statistics Section
Abstract - #306270
Title: An Asymmetric Information Modeling Framework for Ultra-High-Frequency Transaction Data: a Nonlinear Filtering Approach
Author(s): Yoonjung Lee*+
Companies: Harvard University
Address: One Oxford Street, Cambridge, MA, 02138,
Keywords: non-linear filtering ; high-frequency transaction data ; asymmetric information modeling ; market microstructure ; maximum likelihood estimation ; continuous-time finance
Abstract:

The paper proposes a new asymmetric information modeling framework that provides a theoretical explanation for some of the observed interactions among the key quantities in financial markets: the price impact of a trade, the duration between trades, and the degree of information asymmetry. In the model, a private signal is partially revealed through trades, while new public information arrives continuously at the market. The market maker utilizes a non-linear filtering technique to set a competitive price. The pricing rule depends on the actual sequence of order arrivals. The price impact of a trade tends to decrease when the duration between trades gets longer. I provide a procedure to estimate the parameters and discuss the sampling distribution of the parameter estimates.

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