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Identifying Information Types in the Estimation of Informed Trading: An Improved Algorithm

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  • Oguz Ersan

    (International Trade and Finance Department, Faculty of Economics, Administrative and Social Sciences, Kadir Has University, Cibali Mah., Fatih, 34083 Istanbul, Turkey)

  • Montasser Ghachem

    (Department of Economics, Stockholm University, 106 91 Stockholm, Sweden)

Abstract

The growing frequency of news arrivals, partly fueled by the proliferation of data sources, has made the assumptions of the classical probability of informed trading (PIN) model outdated. In particular, the model’s assumption of a single type of information event no longer reflects the complexity of modern financial markets, making the accurate detection of information types (layers) crucial for estimating the probability of informed trading. We propose a layer detection algorithm to accurately find the number of distinct information types within a dataset. It identifies the number of information layers by clustering order imbalances and examining their homogeneity using properly constructed confidence intervals for the Skellam distribution. We show that our algorithm manages to find the number of information layers with very high accuracy both when uninformed buyer and seller intensities are equal and when they differ from each other (i.e., between 86% and 95% accuracy rates). We work with more than 500,000 simulations of quarterly datasets with various characteristics and make a large set of robustness checks.

Suggested Citation

  • Oguz Ersan & Montasser Ghachem, 2024. "Identifying Information Types in the Estimation of Informed Trading: An Improved Algorithm," JRFM, MDPI, vol. 17(9), pages 1-20, September.
    • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:9:p:409-:d:1476590
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    References listed on IDEAS

    as
    1. Michael J. Brennan & Sahn-Wook Huh & Avanidhar Subrahmanyam, 2016. "Asymmetric Effects of Informed Trading on the Cost of Equity Capital," Management Science, INFORMS, vol. 62(9), pages 2460-2480, September.
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    7. Michael J. Brennan & Sahn-Wook Huh & Avanidhar Subrahmanyam, 2018. "High-Frequency Measures of Informed Trading and Corporate Announcements," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2326-2376.
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