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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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 |
work_keys_str_mv |
AT kunlapathsukcharoen analyzingextremecomovementsinagriculturalandenergycommoditymarketsusingaregularvinecopulamethod AT davidleatham analyzingextremecomovementsinagriculturalandenergycommoditymarketsusingaregularvinecopulamethod |
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1724453907500892160 |