Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2418
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dc.contributor.authorDAS, MILAN KUMARen_US
dc.contributor.authorGOSWAMI, ANINDYAen_US
dc.date.accessioned2019-04-02T04:39:15Z
dc.date.available2019-04-02T04:39:15Z
dc.date.issued2019-03en_US
dc.identifier.citationInternational Journal of Financial Engineering, 6(1), 1950006.en_US
dc.identifier.issn2424-7863en_US
dc.identifier.issn2424-7944en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2418
dc.identifier.urihttps://doi.org/10.1142/S2424786319500063en_US
dc.description.abstractWe have developed a statistical technique to test the model assumption of binary regime switching extension of the geometric Brownian motion (GBM) model by proposing a new discriminating statistics. Given a time series data, we have identified an admissible class of the regime switching candidate models for the statistical inference. By performing several systematic experiments, we have successfully shown that the sampling distribution of the test statistics differs drastically, if the model assumption changes from GBM to Markov modulated GBM, or to semi-Markov modulated GBM. Furthermore, we have implemented this statistics for testing the regime switching hypothesis with Indian sectoral indices.en_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publishingen_US
dc.subjectEmpirical volatilityen_US
dc.subjectregime switching GBMen_US
dc.subjecttime series analysisen_US
dc.subjectparameter inferenceen_US
dc.subjectTOC-MAR-2019en_US
dc.subject2019en_US
dc.titleTesting of binary regime switching models using squeeze duration analysisen_US
dc.typeArticleen_US
dc.contributor.departmentDept. of Mathematicsen_US
dc.identifier.sourcetitleInternational Journal of Financial Engineeringen_US
dc.publication.originofpublisherForeignen_US
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