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DC Field | Value | Language |
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dc.contributor.author | Satawat Wannapan | en_US |
dc.contributor.author | Pattaravadee Rakpuang | en_US |
dc.contributor.author | Chukiat Chaiboonsri | en_US |
dc.date.accessioned | 2018-09-05T04:26:01Z | - |
dc.date.available | 2018-09-05T04:26:01Z | - |
dc.date.issued | 2018-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85037852427 | en_US |
dc.identifier.other | 10.1007/978-3-319-70942-0_52 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85037852427&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/58536 | - |
dc.description.abstract | © Springer International Publishing AG 2018. This paper was proposed to computationally investigate the cycling details and risk management of the ASEAN-4 financial stock indexes, including Bangkok Bank (BBL), Development Bank of Singapore Limited (DBS), Commerce International Merchant Bankers (CIMB), and Bank Mandiri (Mandiri). These daily time-series data were observed during 2012 to 2017. Technically, this paper employed the econometric tool called Markov Switching Model (MS-model), the extreme value application called Generalized Pareto Distribution (GPD-model), and the risk management method called Value at Risk (VaR) to provide the estimated solutions and recommendations for investing in these financial stocks. Empirically, the switching regime estimation resulted that these four financial indexes obviously contain real business cycling movements, which were described as bull and bear regimes. Additionally, the results estimated by the GPD model confirmed that there were extreme events inside the trends of the four stock indexes. Ultimately, the outcomes calculated by the risk measurement for extreme cases, which were economic crises, stated that there was an enormously high risk to considerably invest only in short earnings within these four financial stock indexes. Consequently, long-run investment should be mentioned. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Forecasting of VaR in extreme event under economic cycle phenomena for the ASEAN-4 stock exchange | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 753 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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