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DC Field | Value | Language |
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dc.contributor.author | Hung T. Nguyen | en_US |
dc.contributor.author | Nguyen Ngoc Thach | en_US |
dc.date.accessioned | 2019-08-05T04:35:15Z | - |
dc.date.available | 2019-08-05T04:35:15Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85065607496 | en_US |
dc.identifier.other | 10.1007/978-3-030-04200-4_7 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065607496&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/65553 | - |
dc.description.abstract | © Springer Nature Switzerland AG 2019. By taking a closer look at the traditional way we used to proceed to conduct empirical research in economics, especially in using “traditional” proposed models for economical dynamics, we elaborate on current efforts to improve its research methodology. This consists essentially of focusing on the possible use of quantum mechanics formalism to derive dynamical models for economic variables, as well as the use of quantum probability as an appropriate uncertainty calculus in human decision process (under risk). This approach is not only in line with the recent emerging approach of behavioral economics, but also should provide an improvement upon it. For practical purposes, we will elaborate a bit on the concrete road map for applying this “quantum-like” approach to financial data. | en_US |
dc.subject | Computer Science | en_US |
dc.title | A closer look at the modeling of economics data | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 809 | en_US |
article.stream.affiliations | Vietnam National University Ho Chi Minh City | en_US |
article.stream.affiliations | New Mexico State University Las Cruces | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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