Brent Crude

About: Brent Crude is a research topic. Over the lifetime, 548 publications have been published within this topic receiving 9879 citations.

Spillovers between Food and Energy Prices and Structural Breaks

Abstract: This paper estimates a bivariate VAR-GARCH(1,1) model to examine linkages between food and energy prices. The adopted framework is suitable to analyse both mean and volatility spillovers, and also allows for possible parameter shifts resulting from four recent events, namely: 1) the 2006 food crisis, 2) the Brent oil bubble, 3) the introduction of the Renewable Fuel Standard (RFS) policy, and 4) the 2008 global financial crisis. The empirical findings suggest that there are significant linkages between food and both oil and ethanol prices. Further, the four events considered had mixed effects, the 2006 food crisis and 2008 financial crisis leading to the most significant shifts in the (volatility) spillovers between the price series considered.

Modelling commodity value at risk with Psi Sigma neural networks using open–high–low–close data

Abstract: The motivation for this paper is to investigate the use of a promising class of neural network models, Psi Sigma (PSI), when applied to the task of forecasting the one-day ahead value at risk (VaR) of the oil Brent and gold bullion series using open–high–low–close data. In order to benchmark our results, we also consider VaR forecasts from two different neural network designs, the multilayer perceptron and the recurrent neural network, a genetic programming algorithm, an extreme value theory model along with some traditional techniques such as an ARMA-Glosten, Jagannathan, and Runkle (1,1) model and the RiskMetrics volatility. The forecasting performance of all models for computing the VaR of the Brent oil and the gold bullion is examined over the period September 2001–August 2010 using the last year and half of data for out-of-sample testing. The evaluation of our models is done by using a series of backtesting algorithms such as the Christoffersen tests, the violation ratio and our proposed loss functio...

Forecasting the Nominal Brent Oil Price with VARs—One Model Fits All?

Abstract: We carry out an ex post assessment of popular models used to forecast oil prices and propose a host of alternative VAR models based on traditional global macroeconomic and oil market aggregates. While the exact specification of VAR models for nominal oil price prediction is still open to debate, the bias and underprediction in futures and random walk forecasts are larger across all horizons in relation to a large set of VAR specifications. The VAR forecasts generally have the smallest average forecast errors and the highest accuracy, with most specifications outperforming futures and random walk forecasts for horizons up to two years. This calls for caution in reliance on futures or the random walk for forecasting, particularly for near term predictions. Despite the overall strength of VAR models, we highlight some performance instability, with small alterations in specifications, subsamples or lag lengths providing widely different forecasts at times. Combining futures, random walk and VAR models for forecasting have merit for medium term horizons.

Fuel price transmission mechanisms in Portugal

Abstract: This study aims to analyse the behaviour of fuel prices at the pump (unleaded gasoline and diesel) in Portugal, relative to positive and negative variations in Brent crude oil price. Applying an Autoregressive Distributed Lags (ARDL) model to weekly time series data for the period of January 2004 through May 2009, we detected some signs of asymmetry in the transmission price mechanism. However, these patterns are not statistically significant enough to reject hypotheses of symmetry in the price adjustment mechanisms of fuel in Portugal.