Modeling the co-movements between crude oil and refined petroleum markets

Tong, Bin; Wu, Chongfeng; Zhou, Chunyang

doi:10.1016/j.eneco.2013.10.008

Cited by 35 publications

(15 citation statements)

References 37 publications

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“…Copulas are further utilized by Tong et al (2013) who study tail dependence between crude oil and refined petroleum markets. Positive dependence is found in both tails so that the markets tend to move together in both bear and bull periods.…”

Section: Literature Reviewmentioning

confidence: 99%

Leverage effect in energy futures

Krištoufek

2014

Energy Economics

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We propose a comprehensive treatment of the leverage effect, i.e. the relationship between returns and volatility of a specific asset, focusing on energy commodities futures, namely Brent and WTI crude oils, natural gas and heating oil. After estimating the volatility process without assuming any specific form of its behavior, we find the volatility to be longterm dependent with the Hurst exponent on a verge of stationarity and non-stationarity. Bypassing this using by using the detrended cross-correlation and the detrending movingaverage cross-correlation coefficients, we find the standard leverage effect for both crude oil. For heating oil, the effect is not statistically significant, and for natural gas, we find the inverse leverage effect. Finally, we also show that none of the effects between returns and volatility is detected as the long-term cross-correlated one. These findings can be further utilized to enhance forecasting models and mainly in the risk management and portfolio diversification.

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Section: Literature Reviewmentioning

confidence: 99%

Leverage effect in energy futures

Krištoufek

2014

Energy Economics

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“…The VaR model is a good base which can provide us with expected value of the confidence interval from 95% to 99% (Tong et al, 2013). This shows that the use of the historical VaR model for the estimate is a good base for making future decisions of companies.…”

Section: Economics Of Agriculturementioning

confidence: 89%

The effect of crude oil prices fluctuations on the agricultural producers' performance efficiency

Ivanova

Ivanov

Dimitrijević³

2018

Ekonomika poljoprivrede

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The development of agriculture and the security of food supply primarily on the domestic market represent the base of the economic development, and of economic and social stability of a country. Methodology. By using the VaR method, which is the best available risk-measuring technique, the crude oil price fluctuations will be followed in a designated period, in order to understand its influence on the creation of the business policy of agricultural producers. Results. A significant support for the development of agriculture is provided by the leading companies in the crude oil and oil derivatives industry. Conclusions. The aim of the current study is to comprehend the level of influence of crude oil prices as a global economic factor on the behavior of agricultural producers.

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“…Relevant to the question of wholesale-retail price links, Venditti (2013) estimates nonlinear impulse response functions using weekly prices of petroleum, gasoline, and ethanol-gasoline to find asymmetric adjustment in retail prices in the US, but mixed evidence of asymmetric adjustment in selected euro area countries. Tong et al (2013) also estimate…”

Section: Methodsmentioning

confidence: 99%

Biofuel-related price transmission using Renewable Identification Number prices to signal mandate regime

2016

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Rising biofuel use in the United States has raised questions about the interactions between energy and agricultural commodity prices. This expansion of use has been attributed, in part, to tax credits and the Renewable Fuel Standard (RFS). These interventions can lead to questions about whether public policy has helped generate links between energy markets and agricultural markets, with the potential consequence that volatility in one market can be communicated to the 29 other. In this study, we derive theoretical relationships among petroleum, biofuel, and 30 agricultural commodity prices in the context of biofuel mandates, then apply time series methods 31 to estimate the strength of these links. 32 Studies that use historical data often represent market conditions when there were only very small shares of biofuel in liquid fuels and very small shares of feedstocks devoted to biofuel production. In the case of ethanol and corn, for example, the current shares are on the order of ten times their levels in the early 1980s (Figure 1). A key question, then, is whether rising biofuel use has created strong links between petroleum product prices and biofuel feedstock prices. If so, then this finding might lead decision makers to consider the potential for biofuel policies to achieve objectives relating to energy security and greenhouse gas emissions while putting greater weight on impacts of such policies on agricultural commodity price levels and volatility. If 41 biofuels do not create a strong link between petroleum and agricultural crop markets, then the 42 possible impacts on producers and other consumers of agricultural commodities might not be a 43 serious consideration. 44 45

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Modeling the co-movements between crude oil and refined petroleum markets

Cited by 35 publications

References 37 publications

Leverage effect in energy futures

Leverage effect in energy futures

The effect of crude oil prices fluctuations on the agricultural producers' performance efficiency

Biofuel-related price transmission using Renewable Identification Number prices to signal mandate regime

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