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Brent Crude

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


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Journal ArticleDOI
09 Jun 2018
TL;DR: In this article, the authors estimate the volatility of energy futures under different distributions, including gev, gat and alpha-stable distributions, and apply various VaR analyses, such as Gaussian, historical and modified (Cornish-Fisher) VaR, for each variable.
Abstract: Precise modeling and forecasting of the volatility of energy futures is vital to structuring trading strategies in spot markets for risk managers. Capturing conditional distribution, fat tails and price spikes properly is crucial to the correct measurement of risk. This paper is an attempt to model volatility of energy futures under different distributions. In empirical analysis, we estimate the volatility of Natural Gas Futures, Brent Oil Futures and Heating Oil Futures through GARCH and APARCH models under gev, gat and alpha-stable distributions. We also applied various VaR analyses, Gaussian, Historical and Modified (Cornish-Fisher) VaR, for each variable. Results suggest that the APARCH model largely outperforms the GARCH model, and gat distribution performs better in modeling fat tails in returns. Our results also indicate that the correct volatility level, in gat distribution, is higher than those suggested under normal distribution with rates of 56%, 45% and 67% for Natural Gas Futures, Brent Oil Futures and Heating Oil Futures, respectively. Implemented VaR analyses also support this conclusion. Additionally, VaR test results demonstrate that energy futures display riskier behavior than S&P 500 returns. Our findings suggest that for optimum risk management and trading strategies, risk managers should consider alternative distributions in their models. According to our results, prices in energy markets are wilder than the perception of normal distribution. In this regard, regulators and policy makers should enhance transparency and competitiveness in the energy markets to protect consumers.

5 citations

Journal ArticleDOI
Boqiang Lin1, Tong Su1
TL;DR: In this paper, the authors examined the time-varying importance of the six potential factors that drive the Shanghai crude oil futures (INE) prices and found that the pricing effects of these factors almost display upward features within 6 months since the INE establishment.

5 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the spillover effect between Russian index RTS and six futures commodities (Brent oil, natural gas, gasoline, gold, platinum and palladium), observing joint time-frequency domain via wavelet decomposed series.
Abstract: This paper investigates shock and volatility spillover effect between Russian index RTS and six futures commodities (Brent oil, natural gas, gasoline, gold, platinum and palladium), observing joint time-frequency domain via wavelet decomposed series. Due to the fact that our time-span of almost 16 years is permeated with tranquil and crisis periods, we divided full-sample into three subsamples – before, during and after World financial crisis (WFC) via modified ICSS algorithm. We find that spillover effects happen mostly from the commodity markets toward RTS index in all three subsamples. However, during relatively calm periods (first and third sub-periods), spillover effects are very moderate and they occur in relatively few wavelet scales, which points that duration of these effects is limited in peaceful times. On the other hand, duration of spillover effects and its intensity increased during WFC. Also, wavelet coherence indicates that there are areas of stronger co-movements in period of WFC at higher wavelet scales for pairs such as RTS-Brent, -gasoline and -platinum. Commodities that have the strongest transmission effect on RTS index are Brent oil, gasoline and palladium, while gold has strong volatility transmission only during WFC.

5 citations

Journal ArticleDOI
TL;DR: In this article, the performance of commodity cross-hedging of aviation turbine fuel (ATF) price exposures with crude oil and Brent oil futures for the Indian aviation industry was analyzed.
Abstract: This paper analyses the performance of commodity cross-hedging of aviation turbine fuel (ATF) price exposures with crude oil and Brent oil futures for the Indian aviation industry. Models that were estimated using three alternative techniques of ordinary least squares (OLS), error correction models (ECMs), and autoregressive conditional heteroskedastic (ARCH) showed that Brent crude oil futures had the highest cross-hedging efficiency. Further, the variances of the profit and loss (P&L) series and value at risk (VAR) associated with alternative hedging strategies – including a composite hedge of crude oil and Brent oil futures – showed that although hedging is redundant for domestic operations, composite hedging for imported ATF prices could substantially lower the VAR compared to all other alternatives from imported and domestic operations.

5 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202346
202266
202162
202064
201952
201845