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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Hung T. Nguyen | en_US |
| dc.contributor.author | Vladik Kreinovich | en_US |
| dc.contributor.author | Olga Kosheleva | en_US |
| dc.contributor.author | Songsak Sriboonchitta | en_US |
| dc.date.accessioned | 2018-09-04T10:13:14Z | - |
| dc.date.available | 2018-09-04T10:13:14Z | - |
| dc.date.issued | 2015-01-01 | en_US |
| dc.identifier.issn | 16113349 | en_US |
| dc.identifier.issn | 03029743 | en_US |
| dc.identifier.other | 2-s2.0-84951833870 | en_US |
| dc.identifier.other | 10.1007/978-3-319-25135-6_14 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84951833870&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/54421 | - |
| dc.description.abstract | © Springer International Publishing Switzerland 2015. Economic and financial processes are complex and highly nonlinear. However, somewhat surprisingly, linear models like ARMAXGARCH often describe these processes reasonably well. In this paper, we provide a possible explanation for the empirical success of these models. | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Mathematics | en_US |
| dc.title | Why ARMAX-GARCH linear models successfully describe complex nonlinear phenomena: A possible explanation | en_US |
| dc.type | Book Series | en_US |
| article.title.sourcetitle | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
| article.volume | 9376 | en_US |
| article.stream.affiliations | New Mexico State University Las Cruces | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| article.stream.affiliations | University of Texas at El Paso | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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