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Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets

Xiaodong Du and Lihong Lu McPhail

Year: 2012
Volume: Volume 33
Number: Number 2
DOI: 10.5547/01956574.33.2.8
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Abstract:
Motivated by strong comovement and increasing volatility of energy and agricultural prices, we examine dynamic evolutions of ethanol, gasoline, and corn prices over the period of March 2005-March 2011. A structural change is found around March 2008 in the pairwise dynamic correlations between the prices in a multivariate GARCH model. A structural VAR (SVAR) model is then estimated on two subsamples, one before and one after the identified change point. Using the novel method of identification through heteroscedasticity, we exploit the time-varying price volatilities to fully identify the SVAR model. In the more recent period, ethanol, gasoline, and corn prices are found to be more closely linked with a strengthened corn-ethanol relation, which can be largely explained by the new developments of the biofuel industry and related policy instruments. Variance decomposition shows that for each market a significant and relatively large share of the price variation could be explained by the price changes in the other two markets. The results are robust to the inclusion of seasonal dummies and various representative macroeconomic and financial indicators. Keywords: Biofuel, Identification through heteroscedasticity, Structural change, Structural VAR



Oil Prices and the Stock Markets: Evidence from High Frequency Data

Sajjadur Rahman and Apostolos Serletis

Year: 2019
Volume: Volume 40
Number: Special Issue
DOI: 10.5547/01956574.40.SI2.srah
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Abstract:
We use the highest frequency data that have ever been studied before to investigate the relationship between the price of oil and stock market returns. In the context of a bivariate (identified using heteroscedasticity in daily data) structural VAR in stock market returns and the change in the price of oil, we find evidence that positive oil price shocks have negative and statistically significant effects on stock market returns. Our results are robust to the use of different types of market returns, including aggregate and disaggregate U.S. market returns, aggregate and disaggregate U.S. excess returns, returns of the energy sector, returns of the major oil and gas companies, and global, eurozone, and some country specific stock market returns. They are also robust to the use of weekly data.





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