Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54351
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dc.contributor.authorSutthiporn Piamsuwannakiten_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-04T10:12:17Z-
dc.date.available2018-09-04T10:12:17Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-84919360826en_US
dc.identifier.other10.1007/978-3-319-13449-9_18en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84919360826&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54351-
dc.description.abstract© Springer International Publishing Switzerland 2015. This paper presents a CAPM model with a belief function approach for forecasting the Integrated Oil and Gas Company (CHK) stock and the S&P500 index. The approach composed of two steps. First, we estimate the systematic risk or the beta coefficient in the CAPM model using the maximum likelihood method. Second, to improve the forecasting performance, we incorporate the likelihood-based belief functionmethod. Likelihood-based belief functions are calculated from the historical data. The data set contains of 209 weekly returns during the period of 2010–2013. The finding shows evidence on systematic risk which is associated by the belief function derived from the distribution likelihood function given the market return. Finally, we use the method to predict the return of a particular stock.en_US
dc.subjectComputer Scienceen_US
dc.titleForecasting risk and returns: CAPM model with belief functionsen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume583en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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