Noisy Inventory Announcements and Energy Prices

Abstract

This study examines the effect of oil and gas inventory announcements on energy prices. Previous estimates of this effect suffer from bias due to measurement error in inventory surprises. We utilize intraday futures data for three petroleum commodities and natural gas to estimate the price response coefficients using traditional event study regressions and the identification‐through‐censoring (ITC) technique proposed by Rigobon and Sack [Rigobon and Sack (2008). Asset prices and monetary policy (pp. 335–370). Chicago: University of Chicago Press]. The results show that the bias in OLS estimates of the price impact of inventory surprises is quite large. The ITC coefficient estimates are about twice as large as OLS estimates for petroleum commodities and about four times as large as OLS estimates for natural gas. These results imply that energy prices are more strongly influenced by unexpected changes in inventory than shown in previous research. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:911–933, 2014

Asymmetric impacts of fundamentals on the natural gas futures volatility: An augmented GARCH approach

“…Arguably, a more precise method of deriving a surprise variable would be calculating the difference between ex-ante analyst forecasts and ex-post realization of storage level. For example, Gay et al (2009), Bu (2014, and Halova et al (2014) used such forecast data to construct storage surprise variables. We do not have access to well-populated storage forecast data for our sample period but it will be interesting to check the sensitivity of our results to this alternative in a future research.…”

Supply Fundamentals and Grain Futures Price Movements

“…A pseudo R‐squared statistic, showing the fraction of the variance of the dependent variable explained by the model, can be computed as (Halova, Kurov, and Kucher ): where is the estimated variance of the error term through GMM. The ITC method, therefore, allows the computation of a statistic to measure the explanatory power of the fundamentals.…”

“…Because the GMM estimation theory is based asymptotic principles, Halova, Kurov, and Kucher () tested the reliability of the ITC estimates in a finite sample using artificial data and concluded that the ITC estimates were close to the assumed population parameter values.…”

Inventory announcements, jump dynamics, volatility and trading volume in U.S. energy futures markets

“…Furthermore, they provide evidence that prices react strongest to forecasts of analysts with better prior forecast accuracy. Halova et al (2014) provide evidence that previous estimates of the impact of oil and gas inventory surprises' effect on oil and gas price behavior suffer bias due to measurement error in inventory surprises. After correcting the measurement error in the inventory surprise, they show that energy prices are more strongly influenced by unexpected changes in inventory than shown in previous research.…”

“…Previous papers that examine price behavior and volatility surrounding inventory announcements of energy stocks include Linn and Zhu (2004), Gay et al (2009), Halova et al (2014) and others. Linn and Zhu (2004) report an increase in volatility before and after the release of inventory reports by the Energy Information Administration.…”