Showing papers on "Brent Crude published in 2009"
TL;DR: In this paper, a flexible autoregressive conditional heteroskedasticity (ARCH) model is used to take into account the stylized volatility facts such as clustering volatility, asymmetric news impact and long memory volatility among others.
201 citations
TL;DR: The authors examined the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008, and found that the Brent crude oil market is weak-form efficiency while the WTI market seems to be inefficiency on the 1994-2008 sub-period.
81 citations
21 Jun 2009
TL;DR: In this article, the authors used the CAViaR model to evaluate the value-at-risk for daily spot prices of Brent crude oil and West Texas Intermediate crude oil covering the period May 21th, 1987 to Novermber 18th, 2008.
Abstract: This paper uses the Conditional Autoregressive Value at Risk model (CAViaR) proposed by Engle and Manganelli (2004) to evaluate the value-at-risk for daily spot prices of Brent crude oil and West Texas Intermediate crude oil covering the period May 21th, 1987 to Novermber 18th, 2008. Then the accuracy of the estimates of CAViaR model, Normal-GARCH, and GED-GARCH was compared. The results show that all the methods do good job for the low confidence level (95%), and GED-GARCH is the best for spot WTI price, Normal-GARCH and Adaptive-CAViaR are the best for spot Brent price. However, for the high confidence level (99%), Normal-GARCH do a good job for spot WTI, GED-GARCH and four kind of CAViaR specifications do well for spot Brent price. Normal-GARCH does badly for spot Brent price. The result seems suggest that CAViaR do well as well as GED-GARCH since CAViaR directly model the quantile autoregression, but it does not outperform GED-GARCH although it does outperform Normal-GARCH.
8 citations
TL;DR: In this paper, the authors investigated the volatility process of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model, which allows the conditional disturbances to change as time passes and even to switch in different regimes.
Abstract: This paper investigates the volatility process of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model. The SWARCH model allows the conditional disturbances to change as time passes and even to switch in different regimes. The empirical evidence shows that the SWARCH (3,3) model performs the best goodness of fit and the best forecast performance among different fitting models. The estimation of smoothing probabilities of data under different regimes facilitates to capture the characteristics of the data, and the high-volatility regime is associated with some extraordinary events, such as the 1990's Persian Gulf War, the 1997's Asia Financial Crisis, and the 2001's 911 terrorist attack.
3 citations