Estimation of the Probability of Informed Trading Models Via an Expectation-Conditional Maximization Algorithm

dc.authorscopusid 57144228200
dc.authorscopusid 57189005583
dc.contributor.author Ersan, Oğuz
dc.contributor.author Ersan, O.
dc.contributor.other International Trade and Finance
dc.date.accessioned 2025-02-15T19:38:25Z
dc.date.available 2025-02-15T19:38:25Z
dc.date.issued 2025
dc.department Kadir Has University en_US
dc.department-temp Ghachem M., Department of Economics, Stockholm University, Stockholm, 106 91, Sweden; Ersan O., International Trade and Finance Department, Faculty of Economics, Administrative and Social Sciences, Kadir Has University, Istanbul, 34083, Türkiye en_US
dc.description.abstract The estimation of the probability of informed trading (PIN) model and its extensions poses significant challenges owing to various computational problems. To address these issues, we propose a novel estimation method called the expectation-conditional-maximization (ECM) algorithm, which can serve as an alternative to the existing methods for estimating PIN models. Our method provides optimal estimates for the original PIN model as well as two of its extensions: the multilayer PIN model and the adjusted PIN model, along with its restricted versions. Our results indicate that estimations using the ECM algorithm are generally faster, more accurate, and more memory-efficient than the standard methods used in the literature, making it a robust alternative. More importantly, the ECM algorithm is not limited to the models discussed and can be easily adapted to estimate future extensions of the PIN model. © The Author(s) 2025. en_US
dc.description.sponsorship Hakan Bugra Erentug; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (122K637) en_US
dc.description.woscitationindex Social Science Citation Index
dc.identifier.citationcount 0
dc.identifier.doi 10.1186/s40854-024-00729-w
dc.identifier.issn 2199-4730
dc.identifier.issue 1 en_US
dc.identifier.scopus 2-s2.0-85218190052
dc.identifier.scopusquality Q1
dc.identifier.uri https://doi.org/10.1186/s40854-024-00729-w
dc.identifier.volume 11 en_US
dc.identifier.wos WOS:001403162000001
dc.identifier.wosquality Q1
dc.language.iso en en_US
dc.publisher Springer Science and Business Media Deutschland GmbH en_US
dc.relation.ispartof Ficial Innovation en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 0
dc.subject Adjusted Pin Model en_US
dc.subject Ecm en_US
dc.subject Expectation Conditional-Maximization Algorithm en_US
dc.subject Information Asymmetry en_US
dc.subject Maximum-Likelihood Estimation en_US
dc.subject Mpin en_US
dc.subject Multilayer Probability Of Informed Trading en_US
dc.subject Pin Model en_US
dc.subject Private Information en_US
dc.title Estimation of the Probability of Informed Trading Models Via an Expectation-Conditional Maximization Algorithm en_US
dc.type Article en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication
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