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25-09-2023 | Original Research

A new PIN model with application of the change-point detection method

Authors: Chu-Lan Michael Kao, Emily Lin

Published in: Review of Quantitative Finance and Accounting | Issue 4/2023

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Abstract

The existing PIN models impose a restriction on the number of possible intensity pairs. However, our investigation shows that the number of empirical intensity pairs is significantly more than the one these models assume, and this number changes daily. Therefore, we propose a new model which, by using the change-point detection technique, can adjust this number according to the data. The model also considers autocorrelation, which is lacking in the existing PIN models. In addition, we show that the proposed model can examine how public information transfers to individual stock price and quantify transfer delay.

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Appendix
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Metadata
Title
A new PIN model with application of the change-point detection method
Authors
Chu-Lan Michael Kao
Emily Lin
Publication date
25-09-2023
Publisher
Springer US
Published in
Review of Quantitative Finance and Accounting / Issue 4/2023
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-023-01194-9

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