The effect of global oil price shocks on China's agricultural commodities

Zhang, Chuanguo; Qu, Xuqin

doi:10.1016/j.eneco.2015.07.012

Cited by 143 publications

(72 citation statements)

References 49 publications

(53 reference statements)

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“…Our results, notably, are in line with earlier studies . These authors also document the evidence of significant jumps phenomena in energy and biofuel markets.…”

Section: Resultssupporting

confidence: 93%

Carbon emission and ethanol markets: evidence from Brazil

Dutta

Bouri

2018

Biofuels Bioprod Bioref

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The production of ethanol has increased globally over the last decade. It is mainly produced from corn and sugarcane, so earlier studies mainly investigated the impact of food prices on ethanol prices. Although biofuels have been brought into the energy markets to reduce the volume of carbon emissions, the links between ethanol and carbon emission markets have not been explored sufficiently in the existing literature. This study aimed to extend the literature in this field by using a GARCH‐jump process to examine whether Brazilian ethanol prices are affected by carbon emission prices. Our key findings are threefold. First, carbon emission prices affect Brazilian ethanol prices positively. Rising emission prices would therefore cause an increase in the ethanol price. Second, time‐varying jumps occur in the ethanol price index. Third, the impact of emission prices on the ethanol market is asymmetric, implying that increases and decreases in emission prices would have heterogeneous effects on ethanol price levels. Our findings have important implications for scholars, investors, and policymakers. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd

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“…Our results, notably, are in line with earlier studies . These authors also document the evidence of significant jumps phenomena in energy and biofuel markets.…”

Section: Resultssupporting

confidence: 93%

Carbon emission and ethanol markets: evidence from Brazil

Dutta

Bouri

2018

Biofuels Bioprod Bioref

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“…There are two essential reasons for this choice: (a) Corn, wheat, cotton, and soybean futures are very active in China, and the same choice is also made by Li, Zhang, and Zhou (2017), Jiang et al (2016), Tian et al (2017aTian et al ( , 2017b, Yang, Yang, and Zhou (2012), and Zhang and Qu (2015); and (b) the CSI300 index is a well-applied prospect, because it is commonly used as a representative index to measure the overall performance of the Chinese stock market (Chen, Han, Li, & Wu, 2013). There are two essential reasons for this choice: (a) Corn, wheat, cotton, and soybean futures are very active in China, and the same choice is also made by Li, Zhang, and Zhou (2017), Jiang et al (2016), Tian et al (2017aTian et al ( , 2017b, Yang, Yang, and Zhou (2012), and Zhang and Qu (2015); and (b) the CSI300 index is a well-applied prospect, because it is commonly used as a representative index to measure the overall performance of the Chinese stock market (Chen, Han, Li, & Wu, 2013).…”

Section: Preliminary Datamentioning

confidence: 99%

“…In this article, we choose four common agricultural futures-corn, wheat, cotton, and soybean-and the CSI300 index to represent the Chinese agricultural futures market and the stock market. There are two essential reasons for this choice: (a) Corn, wheat, cotton, and soybean futures are very active in China, and the same choice is also made by Li, Zhang, and Zhou (2017), Jiang et al (2016), Tian et al (2017aTian et al ( , 2017b, Yang, Yang, and Zhou (2012), and Zhang and Qu (2015); and (b) the CSI300 index is a well-applied prospect, because it is commonly used as a representative index to measure the overall performance of the Chinese stock market (Chen, Han, Li, & Wu, 2013). The raw transaction prices are obtained from the Wind Financial Terminal in Chinese markets during the period from April 8, 2005, to June 31, 2014.…”

Section: Preliminary Datamentioning

confidence: 99%

The role of jumps in the agricultural futures market on forecasting stock market volatility: New evidence

Zhang

Wahab

et al. 2019

Journal of Forecasting

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In this study, we explore the effect of cojumps within the agricultural futures market, and cojumps between the agricultural futures market and the stock market, on stock volatility forecasting. Also, we take into account large and small components of cojumps. We have several noteworthy findings. First, large jumps may lead to more substantial fluctuations and are more powerful than small jumps. The effect of cojumps and their decompositions on future volatility are mixed. Second, a model including large and small cojumps between the agricultural futures market and the stock market can achieve a higher forecasting accuracy, implying that large and small cojumps contain more useful predictive information than cojumps themselves. Third, our conclusions are robust based on various robustness tests such as the realized kernel, expanding forecasts, different forecasting windows, different jump tests, and different threshold values.

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“…A recent study by Zhang and Qu (2015) investigates the effect of global oil price shocks on agricultural commodities in China, including strong wheat, corn, soybean, bean pulp, cotton, and natural rubber. Considering the oil price volatility process as a combination of continuous process and jump process, the authors document that the oil price is characterized by volatility clustering and jump behavior.…”

Section: Related Literaturementioning

confidence: 99%

Oil and non-energy commodity markets: An empirical analysis of volatility spillovers and hedging effectiveness

Dutta

Noor

2017

Cogent Economics & Finance

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Abstract:Although a large number of empirical papers have examined the price spillover in global oil and non-energy commodity markets, very little is known about the volatility transmission between these two markets. The present study aims to conceal this gap by investigating the volatility cross effects between oil and three different non-energy commodity markets. Using the bivariate VAR-GARCH models, we do not find any evidence of volatility linkage between oil and agricultural product markets during the sample period used. We, however, document that oil market sends volatility to both metal and non-energy aggregate markets. This finding is not surprising, since petroleum-related products are one of the major production inputs in metal industries and hence the production process of metals largely depends on the crude oil market. Since various financial assets are traded on the basis of commodity markets, our results are beneficial for portfolio diversification and hedging decisions. Policy-makers could also use the findings of this research to reduce the impact of oil price uncertainty on metal and agricultural markets. Md Hasib Noor is presently working as an assistant professor in the Faculty of Engineering, American International University Bangladesh. He has published several articles in the field of volatility transmission among financial markets. His current research areas include energy economics and financial market integration. PUBLIC INTEREST STATEMENTThis paper investigates the impact of oil price fluctuations on different non-energy commodity markets. In particular, we consider agriculture, metal, and aggregate non-energy price indices to serve our purpose. Using standard econometric models, we document those variations in oil prices account for the movements in the non-energy commodity prices. Our findings are not surprising, since oil is one of the major production inputs in agriculture and metal markets, and hence oil price shocks impact these non-energy commodity markets. Investors could use our results for making proper investment decisions. In addition, policymakers, on the basis of our results, could take appropriate measures to limit the effect of oil price uncertainty.

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The effect of global oil price shocks on China's agricultural commodities

Cited by 143 publications

References 49 publications

Carbon emission and ethanol markets: evidence from Brazil

Carbon emission and ethanol markets: evidence from Brazil

The role of jumps in the agricultural futures market on forecasting stock market volatility: New evidence

Oil and non-energy commodity markets: An empirical analysis of volatility spillovers and hedging effectiveness

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