Showing papers on "Brent Crude published in 2016"

Time–frequency featured co-movement between the stock and prices of crude oil and gold

Abstract: The nonlinear relationships among variables caused by the hidden frequency information complicate the time series analysis. To shed more light on this nonlinear issue, we examine their relationships in joint time–frequency domain with multivariate framework, and the analyses in the time domain and frequency domain serve as comparisons. The daily Brent oil prices, London gold fixing price and Shanghai Composite index from January 1991 to September 2014 are adopted as example. First, they have long-term cointegration relationship in time domain from holistic perspective. Second, the Granger causality tests in different frequency bands are heterogeneous. Finally, the comparison between results from wavelet coherence and multiple wavelet coherence in the joint time–frequency domain indicates that in the high (1–14 days) and medium frequency (14–128 days) bands, the combination of Brent and gold prices has stronger correlation with the stock. In the low frequency band (256–512 days), year 2003 is the structure broken point before which Brent and oil are ideal choice for hedging the risk of the stock market. Thus, this paper offers more details between the Chinese stock market and the commodities markets of crude oil and gold, which suggests that the decisions for different time and frequencies should consider the corresponding benchmark information.

Fundamentals, Derivatives Market Information and Oil Price Volatility

Abstract: We investigate price volatility in the West Texas Intermediate (WTI) and Brent crude oil markets between 2000 and 2014. We provide empirical evidence of a relationship between the term structure of option-implied volatilities and global macroeconomic conditions, physical market fundamentals (OPEC surplus output capacity, oil storage) and economy-wide financial uncertainty (captured by the equity VIX). Based on public data regarding trader positions in U.S. futures markets, the intensity of oil speculation is statistically insignificant. Unexpected disruptions in the crude oil space are associated with large regression residuals. Our findings suggest that derivatives (“paper”) market contain information on the magnitude and duration of major oil market disruptions.

Affine-Structure Models and the Pricing of Energy Commodity Derivatives

Abstract: We consider a seasonal mean-reverting model for energy commodity prices with jumps and Heston-type stochastic volatility, and three nested models for comparison. By exploiting the affine form of the log-spot models, we develop a general valuation framework for futures and discrete arithmetic Asian options. We investigate five major petroleum commodities from Europe (Brent crude oil, gasoil) and US (light sweet crude oil, gasoline, heating oil) and analyse the effects of the competing fitted spot models in futures pricing, Asian options pricing and hedging. We find evidence that price jumps and stochastic volatility are important features of the petroleum price dynamics.

The influence of macroeconomic factors to the dynamics of stock exchange in the Republic of Kazakhstan

Abstract: This article describes the influence of macroeconomic factors on Kazakhstan Stock Exchange Market by using data from 2005 to 2014. Engle-Granger cointegration test has shown that stock index is cointegrated with the exchange rate, interest rate, CPI and oil price. Vector error correction model has confirmed that macroeconomic variables and the stock index has a long-term equilibrium relationship. Moreover, empirical results have shown that stock index can be used as a leading indicator of the economic situation in Kazakhstan. Therefore, the authors decided to consider the impact of major macroeconomic indicators to the dynamics of the stock market of the Republic of Kazakhstan. The Engle-Granger cointegration test results show that the following variables such as exchange rate, 10-years long-term bond rate, the consumer price index and the Brent oil price are cointegrated with stock index, which means that there is a long-term relationship between this stock market index and these variables. With the help of econometric models, the authors have found the factors such as the exchange rate, the 10-year long-term bonds rate, the consumer price index and the Brent oil price (these factors have the long-term relationship with stock market index). Changes in the dynamics of the stock market index in Kazakhstan are caused by changes in the dynamics of Central bank's reserves and export. The analysis has shown that the economy of the Republic of Kazakhstan (the index reflects the situation in the real sector of the economy) remains dependent on world oil prices, the volume of exports and the rate of the national currency.

An Analysis of the Relationship between Crude Oil Prices, Current Account Deficit and Exchange Rates: Turkish Experiment

Abstract: In this study, the effect of raw oil prices and exchange rates on current account deficit of the Turkish Economy has been examined by investigating the short and long run relationship between the current account deficit of the Turkish Economy, raw oil prices (Brent oil prices) and exchange rates (USD/TRY) The Monthly Data between December 1991 and January 2016 were used in the study The relationships between the variables were tested with the VAR (Vector Auto Regressive) Model None of the series was found stable after the unit root tests, but it was observed that all the variables became stable when their first differences were taken Firstly, an unrestricted VAR model was built to determine the long term relationship between the variables After the long term relationship was found between the variables, the VECM (Vector Error Correction) Model was estimated in order to determine the short term relationship A mutual granger causality relationship is detected between crude oil prices and current account deficit variables No causality relationship is found between the other variables

Using wavelet analysis to uncover the co-movement behavior of multiple energy commodity prices

Abstract: This study aims to investigate the dynamic correlations (co-movement) in between energy commodities such as WTI Crude Oil (WOIL), Brent Crude Oil (BOIL), Heating Oil and Electricity prices. To achieve this goal, we employed partial wavelet coherence (PWC) and multiple wavelet coherence (MWC). Wavelet analysis constitutes the core of these methodologies and MWC is essential to determine the dynamic correlation (co-movement) of time intervals and scales between the time series. We have developed a software program to compute PWC and MWC for quadruple data set. Coherent time intervals of the time series are determined. Vector ARMA models are shown to give a good fit due to having low mean squared errors compared to the univariate case. This allowed us to have better forecast performance.

The impact of Gold, Bond, Currency, Metals and Oil markets on the USA stock market

Abstract: This study examines the impact of financial and economic variables on the industrial Dow Jones Industrial Average (DJIA) using daily data over the sample period March 1995 - May 2014. Gold, Bond, Currency, Metals and Oil market were taken into consideration, and, as well as, their impact on the DJIA. The results of the model GJR – GARCH proved that the purchase of gold, of decade bonds (10 Year Treasury Note) and the U.S. Dollar/Yen exchange rate affect, negatively, the returns of DJIA. On the other hand, it was made clear that the purchase of industrial metals affects, positively, the returns of DJIA. Lastly, our findings indicate that the asymmetry of the oil returns affects- extremely negatively- the DJIA returns. Keywords : GJR-GARCH, Brent oil, Gold, Metals, Equity market, Exchange rates, Bond market, market risk J EL Classifications: C5; G1; G32; R3

On the Predictive Information of Futures' Prices: A Wavelet‐Based Assessment

Abstract: While in speculative markets forward prices could be regarded as natural predictors for future spot rates, empirically, forward prices often fail to indicate ex ante the direction of price movements. In terms of forecasting, the random walk approximation of speculative prices has been established to provide ‘naive’ predictors that are most difficult to outperform by both purely backward-looking time series models and more structural approaches processing information from forward markets. We empirically assess the implicit predictive content of forward prices by means of wavelet-based prediction of two foreign exchange (FX) rates and the price of Brent oil quoted either in US dollars or euros. Essentially, wavelet-based predictors are smoothed auxiliary (padded) time series quotes that are added to the sample information beyond the forecast origin. We compare wavelet predictors obtained from padding with constant prices (i.e. random walk predictors) and forward prices. For the case of FX markets, padding with forward prices is more effective than padding with constant prices, and, moreover, respective wavelet-based predictors outperform purely backward-looking time series approaches (ARIMA). For the case of Brent oil quoted in US dollars, wavelet-based predictors do not signal predictive content of forward prices for future spot prices. Copyright © 2016 John Wiley & Sons, Ltd.

The Relationship between Oil Prices and Exchange Rate in Russia

Abstract: This paper studies the relationship between oil price and the exchange rates in Russian Federation. There is a close interrelation between the currency rate of dollar to ruble and oil prices. The regression model has accurately shown this interrelation. The interrelation with a foreign policy factor - sanctions of the USA and the European Union is also revealed. There is a close interrelation between the currency rate of dollar to ruble and oil prices. The regression model has accurately shown this interrelation. Oil prices of the Brent oil is the dominating factor in a currency exchange rate formation mechanism of ruble, at least, in the long term. When world oil prices are stabilized and sanctions cancelled, currency fluctuations and uncertainty will be minimized. The findings of this paper may be used by foreign and domestic investors while taking decisions because all the shocks impact on the economy in short and long term. Keywords: oil price, exchange rate, interrelation with a foreign policy factor JEL Classifications: C58, F31, Q35

World’s Oil Scenario –Falling Oil Prices Winners and Losers a Study on top Oil Producing and Consuming Countries

Abstract: Global oil prices have fallen sharply over the past seven months, leading to significant revenue shortfalls in many energy exporting nations, while consumers in many importing countries are likely to have to pay less to heat their homes or drive their cars. From 2010 until mid-2015 world oil prices had been fairly stable, at around $110 a barrel. But since June prices have more than halved. Brent crude oil has now dipped below $50 a barrel for the first time since May 2009 and US crude is down to below $48 a barrel.The reasons for this change are twofold - weak demand in many countries due to insipid economic growth, coupled with surging US production. This is the fact that the oil cartel Opec is determined not to cut production as a way to prop up prices.

The relationship between oil and agricultural commodity prices in South Africa : a quantile causality approach

Abstract: The increase in agricultural commodity prices in the recent past has renewed interest in ascertaining the factors that drive agricultural commodity prices. Though a number of factors are possible, higher oil prices are thought to be the major factor driving up agricultural commodity prices, especially as the demand for biofuels production increases. However, empirical evidence of this relationship remain ambiguous and largely depends on the method used. For this reason, there is a need to examine the relationship in the context of different methodologies. Furthermore, information on how South African commodity prices respond to world oil price shocks is less certain. A good understanding of the factors that drive local commodity prices will assist in making sound agricultural policies. In this paper, the Granger causality test is applied to the mean to investigate the causality between oil prices and agricultural (soya beans, wheat, sunflower and corn) commodity prices in South Africa. Daily data spanning from 19 April 2005 to 31 July 2014 is used for Brent crude oil, corn, wheat, sunflower and soya beans prices. Agricultural commodity prices were obtained from the Johannesburg Stock Exchange, and the series of Brent crude oil prices from the U.S. Department of Energy. Results from the linear causality test indicate that oil prices do not influence agricultural commodity prices. However, owing to structural breaks and nonlinear dependence between the variables of study, these results are misleading. As an alternative, the nonparametric test of Granger causality in quantiles, as proposed by Jeong, Hardle and Song (2012) is used. Through this test, we not only look at causality beyond the mean estimates but also accounts for the structural breaks and nonlinear dependence present in the data. Additionally, the method becomes more instructive in the case where the distribution of variables has fat tails. The findings show that the effect of changes in oil prices on agricultural commodity prices vary across the different quantiles of the conditional distribution. The highest impact is not at the median, and the impact on the tails is lower compared to the rest of the distribution. The analysis shows that the relationship between oil prices and agricultural commodity prices depends on specific phases of the market, and therefore contradicts the neutrality hypothesis that oil prices do not cause agricultural commodity prices in South Africa. This implies that policies to stabilize domestic agricultural commodity prices must consider developments in the world oil markets.

Optimal hedge ratio under a subjective re-weighting of the original measure

Abstract: In this article we study a risk-minimizing hedge ratio with futures contracts, where the risk of the hedged portfolio is measured through a spectral risk measure (SRM), thus incorporating the degree of agent’s risk aversion. We empirically estimate the optimal hedge ratio (OHR) using a long time series of UK and US equity indices, the EURUSD and EURGBP exchange rates and four liquid commodities (Brent crude oil, corn, gold and copper), to represent different asset classes. Comparing the results with common OHRs (such as the minimum variance and the minimum expected shortfall), we find that the agent’s risk aversion has a material impact, and should not be ignored in risk management.

Time lags in the pass-through of crude oil prices: big data evidence from the German gasoline market

Abstract: This article investigates the pass-through of global Brent oil notations to fuel prices across the oligopoly of retail majors in Germany. We assemble a high-frequency panel data set that encompasses millions of price observations and allows us to distinguish effects by brand. Upon establishing a cointegrating relationship between fuel and crude oil prices using daily data, we estimate an ECM and find that (1) the pass-through of oil prices critically depends on the number of time lags included in the ECM; (2) strict adherence to classical information criteria for determining lag length yields extremely long pass-through durations and (3) the estimated impulse response functions are virtually identical across brands, irrespective of the lag count, suggesting a high degree of competition among brands.

On the Price–Volume Relationship in Crude Oil Futures Markets

Abstract: This paper applies a quantile regression model to examine the relationship between the contract prices and trading volumes of light sweet crude oil contracts on the New York Mercantile Exchange (NYMEX) and Brent crude oil contracts on the Intercontinental Exchange (ICE). The results show a tandem rise in prices and volumes for light sweet crude oil contracts but a deviation between prices and volumes for Brent crude oil contracts. These two crude oil contracts exhibit significantly different relationships between prices and volumes when prices fluctuate. This finding can help analysts and investors in their investment decisions.

From Oil to Stock Markets

Abstract: This study investigates the impacts of crude oil price variations on the French and American stock market returns using daily observations of Brent crude oil prices, the CAC40, and the Dow Jones Industrial Average indexes for the period of 1999~2012. Our results show strong evidence of fractional cointegration between oil and stock market indices, suggesting the presence of a relationship that governs their long-run joint movements. We find that dynamic correlations increase dramatically during crisis periods, but they move towards their initial levels after those periods. The effect of the lower oil price on the development of the global economy depends not only on whether the low price is expected to be temporary or persistent but also on the causes of the oil price fall. Market analysis shows that the new price levels of oil are caused by the simple mechanism of supply and demand. The low price of oil in 2014 is caused by reduced oil demand because of the slower economic growth in Chinese economy and the impact of developed world’s drive to reduce carbon emissions on the oil market. Given the country-specific dynamic links between oil and stock markets, policymakers may make appropriate policies to reduce the impact of adverse oil price effects on production and economic activities, while investors can optimally design their diversification and hedging strategies, considering oil price persistence patterns.

International Oil Market Risk Anticipations and the Cushing Bottleneck: Option-Implied Evidence

Abstract: We study the equilibrium relationship between the WTI and the Brent crude oil indexes in prices and in option-implied moments using fractional cointegration models from 2008-2016. This period has been subject to changing constraints in terms of rising US inventories and falling demand. Our results suggest there exists a cointegrating relationship in prices as well as between risk-neutral moments. While a long-lasting spread in prices is not supported by the data, our results support a significant volatility differential between the two oil indexes. The Cushing bottleneck is linked to slower speeds of adjustment to disequilibrium for both indexes as well as a fragmentation of the international equilibrium for tail and crash risk, especially for longer horizons. Crash and tail risk are more locally driven and less affected by the international equilibrium than are price and volatility.

Forecast and Backtesting of VAR Models in Crude Oil Market

Abstract: The oil price has a very important effect on the world economy. In this paper, using data sets of Europe Brent and West Texas Intermediate (WTI) Cushing crude oil daily prices from Jan. 4, 2000 to Jan. 4, 2016, the VaR forecasting performance of GARCH-type models are analyzed and compared in a short horizon. Based on the Kupiecs POF-test and Christo ffersens interval forecast test, as well as a Back testing VaR Loss Function, the empirical results indicate that, for Europe Brent crude oil, EGARCH (1,1) has the best performance; while for WTI, APARCH (1,1) and GJR-GARCH (1,1) outperform other GARCH models. In fact, these results also give significant guidance on how to choose a better risk management model for the certain commodity of different companies even in the same time period.

Elucidating the Relationship among EUA Spot Price, Brent Oil Price and Three European Stock Indices

Abstract: For decades, humans have been consuming large quantities of oil, coal and natural gas. Consequently, people must now take responsibility for having participated in productive activities that have caused the emissions of greenhouse gas (GHG) which has damaged the environment and caused problems associated with abnormal weather. Previous studies investigated the relationships between energy and carbon prices, between oil price and stock index, or between carbon price and macro-economic factors. Few have examined the relationships among EUA spot price, oil price and the stock index in individual nations. Owing to the fact that the European Emissions Trading Scheme (EU ETS) is the world's first carbon market and remains the largest globally, this study, based on the finding of Chevallier (2009) that capital markets are closely related to the commodity markets, examines the long-term equilibrium relationship and causality among European Union Allowance (EUA) spot price, Brent oil price and three European major stock indices from January 1, 2005 to Dec. 31, 2012. The sample period is further divided into three sub-periods of 2005 to 2007 (Phase 1 of the EU ETS), 2008 to 2010 (US subprime loan crisis and the first period of Phase 2 of the EU ETS), and 2011 to 2012 (European debt crisis and the second period of Phase 2 of the EU ETS). Numerous notable findings from the empirical findings are presented. First, EUA spot price, oil price and DAX index are co-integrated with each other during the second sub-period. Although oil price can be adjusted to the long-term equilibrium in German stock market during that period, adjusting EUA spot price to long-term equilibrium is rather difficult. Next, oil price is affected by EUA spot price unilaterally for the full sample period and the third sub-period. Moreover, EUA spot price is unaffected by any factor except itself during the first sub-period, and is affected by three European stock indices for the full sample period, and the third sub-period. Furthermore, the most explanatory power for Brent oil and EUA spot prices arises from themselves, respectively. Finally, the capital markets and commodity markets are closely related during the 2nd sub-period only.

Negative oil price bubble is likely to burst in March - May 2016. A forecast on the basis of the law of log-periodical dynamics

Abstract: Data analysis with log-periodical parametrization of the Brent oil price dynamics has allowed to estimate (very approximately) the date when the dashing collapse of the Brent oil price will achieve the absolute minimum level (corresponding to the so-called singularity point), after which there will occur a rather rapid rebound, whereas the accelerating fall of the oil prices which started in mid-2014 will come to an end. This is likely to happen in the period between March, 24th and May, 15th, 2016. An analogous estimate (though a more exact one) was made for the date of the burst of the nearest negative "sub-bubble", which is likely to occur between 19.01 and 02.02.2016 (importantly, this estimate will allow to verify the robustness of the developed forecast in the very nearest days). However, this will not mean a start of a new uninterrupted global growth - the fall will soon continue, breaking new "anti-records". The fall will only finally stop after passing the abovementioned point of the main negative bubble singularity somewhere between March 24th and May 15th, 2016 (if, of course, the oil market remains at the disposal of speculators, and no massive interventions of macro actors are made). Importantly, our calculations have also shown that after mid-2014 we are dealing not with an antibubble (when price collapse goes on in a damped and almost unstoppable regime) in the world oil market, but with a negative bubble, when prices collapse in an accelerated mode, and there can be particularly powerful collapses with particularly strong destabilizing effect near the singularity point. On the other hand, negative bubbles can be better manipulated by the actions of the macro actors.

Pemodelan dan peramalan indeks harga saham gabungan (ihsg), jakarta islamic index (jii), dan harga minyak dunia brent crude oil menggunakan metode vector autoregressive exogenous (varx)

Abstract: Index of stocks listed on the Indonesia Stock Exchange (IDX) there are conventional that one of them is the Composite Stock Price Index (CSPI) and the index of stocks that are sharia is the Jakarta Islamic Index (JII). In its movement, the value of CSPI and JII often increases and decreases that are influenced by several factors, one of which is the world oil price of Brent Crude Oil . To see the value of CSPI and JII conditions during the period of the next few months it takes the model equations. Because the third such data included in the time series data, we used time series analysis with the appropriate method is the Vector Autoregressive Exogenous (VARX). VARX( p , q ) is a model of multivariate time series that consists of several endogenous variable of the time series order p with q adding exogenous variables. The purpose of this study is to obtain an appropriate VARX models and forecasting for data CSPI and JII. The model to predict CSPI and JII with exogenous variables that influence the world oil prices of Brent Crude Oil is VARX(1,1). Test parameters for exogenous variables in the model VARX(1,1) not significant at significance level α = 5%, but this result could be ignored and continues to testing residual assumptions. Residual model VARX(1,1) satisfies the assumption of white noise and multivariate normal distribution, in order to obtain results as very good forecast that with each MAPE value for CSPI and JII forecast of 2,71% and 3,63%. Keywords : CPSI, JII, Brent Crude Oil , VARX, MAPE.

Analysis of Spanish Wholesale Gas Price Determinants and Non-stationarity Effects for Modelling

Abstract: This study expands on previous research on Spanish gas prices by investigating on the nature of the existing relationships with its main determinants and with special attention to Brent oil price relationship. The study focus on capturing the best representation of the main drivers behind SGP movements as a sensible step towards a more complex modelling exercise to explain Spanish gas pricing mechanics. In addition the analysis does also seek to better understand long-term persistence properties of SGP to obtain a view of how and to what extent those are transmitted through links with other primary energy commodities. Results from our investigation show that when comparing the different lags of Brent oil prices fitting normalized gas prices, the proxy best representing crude oil price is close to a Brent price lagging six months with validity for the next three months. Results for generic unit root tests indicate that all the series analysed are stationary in first differences logarithm what would open scope for using cointegration methods to study SGP long-run dynamics in the future.

Explaining the oil price spread between WTI and Brent during U.S. shale oil revolution

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