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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. [ABSTRACT FROM AUTHOR]

We empirically reinvestigate the issue of the excess co-movement of commodity prices initially raised in Pindyck and Rotemberg (1990). Excess co-movement appears when commodity prices remain correlated even after adjusting for the impact of fundamentals. We use recent developments in large approximate factor models to consider a richer information set and adequately model these fundamentals. We consider a set of eight unrelated commodities along with 184 real and nominal macroeconomic variables, from developed and emerging economies, from which nine factors are extracted over the 1993-2013 period. Our estimates provide evidence of time-varying excess co-movement which is particularly high after 2007. We further show that speculative intensity is a driver of the estimated excess comovement, as speculative trading is both correlated across the commodity futures markets and correlated with the futures prices. Our results can be taken as direct evidence of the significant impact of financialization on commodity-price crossmoments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]