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DC Field | Value | Language |
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dc.contributor.author | Kittawit Autchariyapanitkul | en_US |
dc.contributor.author | Somsak Chanaim | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2018-09-04T10:12:26Z | - |
dc.date.available | 2018-09-04T10:12:26Z | - |
dc.date.issued | 2015-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-84919360816 | en_US |
dc.identifier.other | 10.1007/978-3-319-13449-9_15 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84919360816&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/54360 | - |
dc.description.abstract | © Springer International Publishing Switzerland 2015. We used a quantile regression under asymmetric Laplace distribution for predicting stock returns. Specifically, we apply this method to the classical capital asset pricing model (CAPM) to estimate the beta coefficient which measure risk in the portfolios management analysis at given levels of quantile. Quantile regression estimation is equivalent to the parametric case where the error term is asymmetrically Laplace distributed. Finally, we use the method to measures the volatility of a portfolio relative to the market. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Quantile regression under asymmetric laplace distribution in capital asset pricing model | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 583 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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