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

Chu-Lan Michael Kao () and Emily Lin ()
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Chu-Lan Michael Kao: National Yang Ming Chiao-Tung University
Emily Lin: St. John’s University

Review of Quantitative Finance and Accounting, 2023, vol. 61, issue 4, No 11, 1513-1528

Abstract: 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.

Keywords: Probability of informed trading (PIN); Change-point detection technique; Information transfer delay (search for similar items in EconPapers)
JEL-codes: G14 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11156-023-01194-9

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