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DC Field | Value | Language |
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dc.contributor.author | DAS, MILAN KUMAR | en_US |
dc.contributor.author | GOSWAMI, ANINDYA | en_US |
dc.date.accessioned | 2019-04-02T04:39:15Z | |
dc.date.available | 2019-04-02T04:39:15Z | |
dc.date.issued | 2019-03 | en_US |
dc.identifier.citation | International Journal of Financial Engineering, 6(1), 1950006. | en_US |
dc.identifier.issn | 2424-7863 | en_US |
dc.identifier.issn | 2424-7944 | en_US |
dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2418 | |
dc.identifier.uri | https://doi.org/10.1142/S2424786319500063 | en_US |
dc.description.abstract | We 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.iso | en | en_US |
dc.publisher | World Scientific Publishing | en_US |
dc.subject | Empirical volatility | en_US |
dc.subject | regime switching GBM | en_US |
dc.subject | time series analysis | en_US |
dc.subject | parameter inference | en_US |
dc.subject | TOC-MAR-2019 | en_US |
dc.subject | 2019 | en_US |
dc.title | Testing of binary regime switching models using squeeze duration analysis | en_US |
dc.type | Article | en_US |
dc.contributor.department | Dept. of Mathematics | en_US |
dc.identifier.sourcetitle | International Journal of Financial Engineering | en_US |
dc.publication.originofpublisher | Foreign | en_US |
Appears in Collections: | JOURNAL ARTICLES |
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