Title

Modelling Trade Direction with Autoregressive Conditional Marked Duration and the Probability of Informed Trading

Publication Type

Journal Article

Publication Date

2009

Abstract

This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades jointly. Unlike the Easley, Hvidkjaer, and O’Hara (2002) approach, which uses the aggregate numbers of daily buy and sell orders to estimate PIN, our methodology allows for interactions between consecutive buy-sell orders and accounts for the duration between trades and the volume of trade. We extend the Easley– Hvidkjaer–O’Hara framework by allowing the probabilities of good news and bad news to vary each day. Our PIN estimates can be computed daily as well as over intraday intervals.

Discipline

Econometrics | International Economics

Research Areas

Econometrics

Publication

Journal of Financial Econometrics

Volume

7

Issue

3

First Page

288

Last Page

311

ISSN

1479-8409

Identifier

10.1093/jjfinec/nbp005

Publisher

Oxford University Press

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1093/jjfinec/nbp005

This document is currently not available here.

Share

COinS