Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method

<p>Using a regular vine copula approach, this paper analyzes the dependence structure and tail dependence patterns among daily prices of three agricultural commodities (corn, soybean, and wheat) and two energy commodities (ethanol and crude oil) from June 2006 to June 2016. Our findings sugges...

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Main Authors: Kunlapath Sukcharoen, David Leatham
Format: Article
Language:English
Published: EconJournals 2018-09-01
Series:International Journal of Energy Economics and Policy
Online Access:https://www.econjournals.com/index.php/ijeep/article/view/6804
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spelling doaj-36629f8e29c945eebc433e74d4995c0a2020-11-25T03:59:36ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532018-09-01851932013478Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula MethodKunlapath Sukcharoen0David Leatham1West Texas A&M UniversityTexas A&M University<p>Using a regular vine copula approach, this paper analyzes the dependence structure and tail dependence patterns among daily prices of three agricultural commodities (corn, soybean, and wheat) and two energy commodities (ethanol and crude oil) from June 2006 to June 2016. Our findings suggest that the prices of corn and crude oil are linked through the ethanol market, which are consistent with the results from previous studies. We also find that crude oil and agricultural commodity prices are statistically dependent during the extreme market downturns but independent during the extreme market upturns. In addition, the results from our sub-sample analysis show that both the upper and lower tail dependence between crude oil and other commodity markets become weaker in the recent years when the ethanol market became more mature.</p><p><strong>Keywords: </strong>Agricultural Markets, Energy Markets, Price Dependence, Tail Dependence, Vine Copulas</p><p><strong>JEL Classifications: </strong>C53, C58, G11, G17, Q13, Q40<strong></strong></p>https://www.econjournals.com/index.php/ijeep/article/view/6804
collection DOAJ
language English
format Article
sources DOAJ
author Kunlapath Sukcharoen
David Leatham
spellingShingle Kunlapath Sukcharoen
David Leatham
Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
International Journal of Energy Economics and Policy
author_facet Kunlapath Sukcharoen
David Leatham
author_sort Kunlapath Sukcharoen
title Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
title_short Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
title_full Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
title_fullStr Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
title_full_unstemmed Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method
title_sort analyzing extreme comovements in agricultural and energy commodity markets using a regular vine copula method
publisher EconJournals
series International Journal of Energy Economics and Policy
issn 2146-4553
publishDate 2018-09-01
description <p>Using a regular vine copula approach, this paper analyzes the dependence structure and tail dependence patterns among daily prices of three agricultural commodities (corn, soybean, and wheat) and two energy commodities (ethanol and crude oil) from June 2006 to June 2016. Our findings suggest that the prices of corn and crude oil are linked through the ethanol market, which are consistent with the results from previous studies. We also find that crude oil and agricultural commodity prices are statistically dependent during the extreme market downturns but independent during the extreme market upturns. In addition, the results from our sub-sample analysis show that both the upper and lower tail dependence between crude oil and other commodity markets become weaker in the recent years when the ethanol market became more mature.</p><p><strong>Keywords: </strong>Agricultural Markets, Energy Markets, Price Dependence, Tail Dependence, Vine Copulas</p><p><strong>JEL Classifications: </strong>C53, C58, G11, G17, Q13, Q40<strong></strong></p>
url https://www.econjournals.com/index.php/ijeep/article/view/6804
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AT davidleatham analyzingextremecomovementsinagriculturalandenergycommoditymarketsusingaregularvinecopulamethod
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