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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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DOI
01 Jan 2018
TL;DR: In this paper, the authors compared different newer models (e.g. CAViaR and one of the most recent approaches HAR-QREG) to the more traditional approaches for value at risk calculation, and found that the newer models are able to outperform the traditional approaches, but all fail to model corn return due to an extreme price drop.
Abstract: We compared different newer models (e.g. CAViaR and one of the most recent approaches HAR-QREG) to the more traditional approaches (e.g. RiskMetrics and GARCH(1,1)) for value at risk calculation. As samples for different asset classes we chose MDAX and CDAX as representatives for the German capital market, gold, Brent crude oil, wheat, and corn for alternative investments, and the EUR/USD exchange rate representing the currency market. The prediction quality of each model was tested using back testing methods like the conditional coverage and dynamic quantile test. It turned out that the newer models are able to outperform the traditional approaches, but all fail to model corn return due to an extreme price drop.
Book ChapterDOI
01 Jan 2015
TL;DR: In this paper, the authors examined the influence of OPEC quota decisions on the stock price of four typical listed oil firms in Europe and considered the influence on the Brent crude oil price.
Abstract: This study examines the influence of OPEC quota decisions (quota cut—increase or unchanged decision) on the stock price of four typical-listed-oil firms in Europe. In addition, we consider the influence on the Brent crude oil price. Using the event study methodology, 51 announcements are considered in the period 1991–2012. The results imply that OPEC quota decisions have a direct influence on both crude oil returns and oil firms’ stock returns. This influence is either positive or negative and large or small, depending on the type of decision and the size of the firms in terms of market capitalization. However, since the difference between the two small firms is also significant, we conclude that market capitalization alone is not a determining factor.
Journal Article
TL;DR: In this article, a variety of GARCH models using weekly closing price (in USD/barrel) of Brent crude oil and weekly closing prices of coffee Arabica, and compared the forecasting performance of these models based on a high frequency intra-day data which allows for a more precise realized volatility measurement.
Abstract: Modeling, analyzing, and forecasting volatility has been the subject of extensive research among academics, practitioners and portfolio managers This paper estimates a variety of GARCH models using weekly closing price (in USD/barrel) of Brent crude oil and weekly closing prices (in USD/pound) of coffee Arabica, and compares the forecasting performance of these models based on a high frequency intra-day data which allows for a more precise realized volatility measurement The study used weekly price data to explicitly model volatility, and employed high-frequency intra-day data to assess model forecasting performance The analysis points to the conclusion that GARCH (1,1) for Arabica coffee and GARCH (1,2) crude oil returns were best models, respectively with Student’s t distributed innovation terms is the most accurate volatility forecasting models in the context of our empirical setting We recommend and encourage future researchers studying the forecasting performance of GARCH models to pay particular attention to the measurement of realized volatility, and employ high-frequency data whenever feasible
Journal ArticleDOI
TL;DR: In this article , the authors explored the relationship between production and price, specifically that of crude oil, and investigated whether and how the changes in monthly crude oil production by OPEC and non-OPEC members in Europe, America, and Asia have affected the changes of three major crude oil prices, namely, WTI, Brent, and Dubai, in the following terms.
Abstract: This work explores the relationship between the price of crude oil and its production through an empirical study on the regions of the Organization of the Petroleum Exporting Countries (OPEC) and non-Organization of the Petroleum Exporting Countries (non-OPEC). The crude oil price has recently been fluctuating greatly that it cannot be predicted; this fluctuation causes changes in the prices of raw materials for everyday life, thus affecting the economy worldwide. To better understand the factors that affect the crude oil price, this study gathered monthly oil production by OPEC and non-OPEC members, which are divided into the regions of Europe, America, and Asia according to the U.S. Energy Information Administration (2015). Data on the West Texas Intermediate (WTI), Brent, and Dubai oil prices in the period from January 1995 to November 2015 were also gathered and subjected to unbalanced panel random effect regression to investigate the relationship between crude oil price and oil production and to determine whether the oil production by these countries have a significant effect on the fluctuation of crude oil price. This study explored the relationship between production and price, specifically that of crude oil. Hence, it investigated whether and how the changes in monthly crude oil production by OPEC and non-OPEC members in Europe, America, and Asia have affected the changes in three major crude oil prices, namely, WTI, Brent, and Dubai, in the following terms.

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