An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model

This paper aims to study the structure of interdependencies between the energy, biofuel and agricultural commodity markets. The work concentrates on the dependence between ethanol and agricultural futures returns conditional to crude oil returns, and interdependence among agricultural commodities co...

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Main Authors: Phattanan Boonyanuphong, Songsak Sriboonchitta
Format: Book Series
Published: 2018
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897874778&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45618
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-456182018-01-24T06:13:55Z An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model Phattanan Boonyanuphong Songsak Sriboonchitta This paper aims to study the structure of interdependencies between the energy, biofuel and agricultural commodity markets. The work concentrates on the dependence between ethanol and agricultural futures returns conditional to crude oil returns, and interdependence among agricultural commodities conditional to crude oil and ethanol futures returns. The C-vine copula based ARMA-GARCH model was used to explain the dependence structure of crude oil and the four related variables, and applied to investigate the risk of energy-agricultural commodity futures portfolio. We generally found symmetry in the tail dependence between the energy, biofuel, and agricultural commodities, and also found a greater significant variability in dependence, specifically, the dependence between the ethanol and agricultural commodity futures returns conditional to crude oil as well as interdependence between corn and soybean conditional to crude oil and ethanol return. This indicates that there is a rise in ethanol productions and that higher crude oil prices have caused a price increase in agricultural commodities such as corn and soybean. Moreover, the higher dynamic dependence and symmetric tail dependences indicate that opportunities for portfolio diversification are reduced, particularly during a downturn in the markets. Finally, our result suggests that the time-varying copula model captures the portfolio risk better than the static copula models. © Springer International Publishing Switzerland 2014. 2018-01-24T06:13:55Z 2018-01-24T06:13:55Z 2014-01-01 Book Series 21945357 2-s2.0-84897874778 10.1007/978-3-319-03395-2_26 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897874778&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45618
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description This paper aims to study the structure of interdependencies between the energy, biofuel and agricultural commodity markets. The work concentrates on the dependence between ethanol and agricultural futures returns conditional to crude oil returns, and interdependence among agricultural commodities conditional to crude oil and ethanol futures returns. The C-vine copula based ARMA-GARCH model was used to explain the dependence structure of crude oil and the four related variables, and applied to investigate the risk of energy-agricultural commodity futures portfolio. We generally found symmetry in the tail dependence between the energy, biofuel, and agricultural commodities, and also found a greater significant variability in dependence, specifically, the dependence between the ethanol and agricultural commodity futures returns conditional to crude oil as well as interdependence between corn and soybean conditional to crude oil and ethanol return. This indicates that there is a rise in ethanol productions and that higher crude oil prices have caused a price increase in agricultural commodities such as corn and soybean. Moreover, the higher dynamic dependence and symmetric tail dependences indicate that opportunities for portfolio diversification are reduced, particularly during a downturn in the markets. Finally, our result suggests that the time-varying copula model captures the portfolio risk better than the static copula models. © Springer International Publishing Switzerland 2014.
format Book Series
author Phattanan Boonyanuphong
Songsak Sriboonchitta
spellingShingle Phattanan Boonyanuphong
Songsak Sriboonchitta
An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
author_facet Phattanan Boonyanuphong
Songsak Sriboonchitta
author_sort Phattanan Boonyanuphong
title An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
title_short An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
title_full An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
title_fullStr An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
title_full_unstemmed An analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
title_sort analysis of interdependencies among energy, biofuel, and agricultural markets using vine copula model
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84897874778&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/45618
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