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dc.contributor.authorChatchai Khiewngamdeeen_US
dc.contributor.authorQuanrui Songen_US
dc.contributor.authorSomsak Chanaimen_US
dc.date.accessioned2018-09-05T04:26:13Z-
dc.date.available2018-09-05T04:26:13Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85044004706en_US
dc.identifier.other10.1007/978-3-319-75429-1_32en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85044004706&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58555-
dc.description.abstract© 2018, Springer International Publishing AG, part of Springer Nature. This paper aims to investigate whether including agricultural commodities can improve the portfolio performance by comparing the risk and return of multi-asset portfolio with and without an agricultural commodity price. To achieve our goal, we propose fitting a C-Vine copula based AR-GARCH model to interval data which allows us to capture uncertain characteristics that cannot be sometimes fully described with single data series. By using a convex combination method, we can obtain expected marginal distribution and joint density function, respectively. We then evaluate the portfolios’ risk and return using the expected shortfall concept. The results present that the average risk and return of non-agricultural portfolio outperforms agricultural portfolios. However, considering the one step ahead forecasting efficient frontier, the portfolio with soybean futures becomes superior to other portfolios.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleThe Role of Agricultural Commodity Prices in a Portfolioen_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume10758 LNAIen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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