This study investigates how prices respond to unanticipated crude oil inventory shocks and how quickly the markets incorporate news in crude oil, gasoline, and heating oil futures markets by using structured vector autoregression (SVAR) models based on EIA inventory report announcement and news...

This study investigates how prices respond to unanticipated crude oil inventory shocks and how quickly the markets incorporate news in crude oil, gasoline, and heating oil futures markets by using structured vector autoregression (SVAR) models based on EIA inventory report announcement and news...

This paper develops an empirical cost of carry model with endogenously conditioned convenience yield. The approach is implemented using monthly prices of all futures contracts traded at the New York Mercantile Exchange between 1985 and 2006. Tests indicate that the model fits the data extremely...

The paper contributes to the rare literature modeling term structure of crude oil markets. We explain term structure of crude oil prices using dynamic Nelson-Siegel model, and propose to forecast them with the generalized regression framework based on neural networks. The newly proposed...

We study the impact of analyst forecasts on prices to determine whether investors learn about analyst accuracy. The straight-forward relationship between supply and price, the economic importance of the market, the predictable timing of forecast error realizations, and the high frequency of the...