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Fundamental and Financial Influences on the Co-movement of Oil and Gas Prices

Derek Bunn, Julien Chevallier, Yannick Le Pen, and Benoit Sevi

Year: 2017
Volume: Volume 38
Number: Number 2
DOI: 10.5547/01956574.38.2.dbun
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Abstract:
As speculative flows into commodity futures are expected to link commodity prices more strongly to equity indices, we investigate whether this process also creates increased correlations amongst the commodities themselves. Considering U.S. oil and gas futures, we investigate whether common factors, derived from a large international data set of real and nominal macroeconomic variables by means of the large approximate factor models methodology, are able to explain both returns and whether, beyond these fundamental common factors, the residuals remain correlated. We further investigate a possible explanation for this residual correlation by using some proxies for trading intensity derived from CFTC publicly available data, showing most notably that the proxy for speculation in the oil market increases the oil-gas correlation. We thus identify the central role of financial activities in shaping the link between oil and gas returns.



Informed Trading in the WTI Oil Futures Market

Olivier Rousse and Benoit Sevi

Year: 2019
Volume: Volume 40
Number: Number 2
DOI: 10.5547/01956574.40.2.orou
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Abstract:
The weekly release of the U.S. inventory level by the DOE-EIA is known as the market mover in the U.S. oil futures market. We uncover suspicious trading patterns in the WTI futures markets in days when the inventory level is released that are higher than market forecasts: there are significantly more orders initiated by buyers in the two hours preceding the official release of the inventory level, with a drop in the average price of -0.25% ahead of the news release. This finding is consistent with informed trading. We also provide evidence of an asymmetric response of the oil price to oil-inventory news, and highlight an over-reaction that is partly compensated in the hours following the announcement.



How are Day-ahead Prices Informative for Predicting the Next Day's Consumption of Natural Gas? Evidence from France

Arthur Thomas, Olivier Massol, Benoît Sévi

Year: 2022
Volume: Volume 43
Number: Number 5
DOI: 10.5547/01956574.43.5.atho
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Abstract:
The purpose of this paper is to investigate, for the first time, whether the next day’s consumption of natural gas can be accurately forecast using a simple model that solely incorporates the information contained in day-ahead market data. Hence, unlike standard models that use a number of meteorological variables, we only consider two predictors: the price of natural gas and the spark ratio measuring the relative price of electricity to gas. We develop a suitable modeling approach that captures the essential features of daily gas consumption and, in particular, the nonlinearities resulting from power dispatching and apply it to the case of France. Our results document the existence of a long-run relation between demand and spot prices and provide estimates of the marginal impacts that these price variables have on observed demand levels. We also provide evidence of the pivotal role of the spark ratio in the short run which is found to have an asymmetric and highly nonlinear impact on demand variations. Lastly, we show that our simple model is sufficient to generate predictions that are considerably more accurate than the forecasts published by infrastructure operators.





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