WTI Oil Prices Research Articles

Empirical analysis of the dynamic dependence between WTI oil and Chinese energy stocks

In this paper, we employ the dynamic copula approach to explore the dependence structure between WTI oil and Chinese energy stock index (300ENI). We first use the AIC (Akaike Information Criteria) together with the binary segmentation procedure to detect the change points of copula families and copula parameters, which extend the existing time-varying copula method. Then we can get the optimal copula between WTI oil and 300ENI for each time period, and analyze the dependence between them combining with the national and international economic environment. We find that the recession of both the international oil market and Chinese energy stock market causes the significant concordance and symmetric tail dependence. The asymmetric dependence turns out to be in Chinese economic recession and recovery time. Furthermore, we apply our results to analyze the effectiveness of hedging WTI oil using 300ENI. Results show that the hedging is more effective in China's sluggish time than in economic boom. Finally, our economic cycle analysis shows that different economic situation pairs of WTI oil and Chinese energy stocks exhibit different tail dependency, which could be used to predict the market future and provide market participants and policy makers with some suggestions on investment, hedging and decision making. • The dynamic copula with change in parameters and types is modeled. • A new method of applying Akaike Information Criterion into binary segmentation procedure is proposed. • The relationship between WTI oil prices and 300ENI returns have been studied. • Different economic state pairs of two markets exhibit different concordance and tail dependency. • The proposed model is applied to calculate the hedge ratio and hedging effectiveness of 300ENI against the WTI oil risk.

Asymmetric Impacts of Oil Price on Inflation: An Empirical Study of African OPEC Member Countries

This study investigates the asymmetric impacts of oil price changes on inflation in Algeria, Angola, Libya, and Nigeria. Three different kinds of oil price data were applied in this study: the actual spot oil price of individual countries, the OPEC reference basket oil price, and an average of the Brent, WTI, and Dubai oil price. Autoregressive distributed lag (ARDL) dynamic panels were used to estimate the short- and long-term impacts. Also, we partitioned the oil price into positive and negative changes to capture asymmetric impacts and found that both the positive and negative oil price changes positively influenced inflation. However, the impact was found to be more significant when the oil prices dropped. We also found that the money supply, the exchange rate, and the gross domestic product (GDP) are positively related to inflation, while food production is negatively related to inflation. Accordingly, policy-makers should be cautious when formulating policies between the positive and negative changes in oil prices, as it was shown that inflation increased when the oil price dropped. Additionally, the use of a contractionary monetary policy would help to reduce the inflation rate. Lastly, we suggest that the government should encourage domestic food production, both in quantity and quality, to reduce inflation.

VOLATILITY OF CRUDE OIL PRICES, FOREIGN EXCHANGE EXPOSURES, AND COMPANY’S PERFORMANCE: EMPIRICAL EVIDENCE FROM TAIWANESE 3PL INDUSTRY

Purpose of the study: In this paper, we investigate the impact of the changes in crude oil prices and fluctuation of foreign exchange rate on the operating performances of Taiwanese 3PL industry.Methodology: Vector Autoregression Models. Through the empirical model, we find that all the 3PL companies are more suffered to the volatility of WTI and Dubai crude oil prices, but Dubai is insignificant to the warehousing companies. In the fluctuations of foreign exchange rate, some have positive effect and some are negative.Main Findings: All the Taiwanese 3PL companies are more suffered to the volatility of WTI and Dubai crude oil prices, however Dubai is insignificant to the warehousing companies. Moreover, we find an interesting result, that is, for some companies operating performance, the impact on the volatilities of crude oil have the same sign but in opposite direction. For example, in our empirical results, the stock returns are positively correlated to volatilities of Dubai and Brent crude oil prices, however, WTI’s volatility has negative impact on them.Implications: It implies that the company can make a “natural hedge” strategy to hedge the crude oil volatility risk by forming a portfolio which pools these three commodities together. In this way, we made recommendations to the company’s decision-making reminding that the company should make a portfolio of foreign exchange and crude oil price fluctuations in the hedge strategy to enhance the company’s risk management operations and to reduce the loss caused by these factors.Novelty/Originality of this study: This study contributes in the existing literature for an empirically study of a firm-level evidence from Taiwanese 3PL companies.

U.S. shale oil production and WTI prices behaviour

The aim of this paper is to relate the shale oil revolution in the United States with WTI oil price behavior. Since the development of the combination of horizontal drilling techniques together with hydraulic fracturing in the 1970s, known as shale oil, oil markets have undergone a significant transformation with the unexpectedly strong rise in the United States production affecting oil prices. The goal of this paper is two-fold: first, we analyze the relationship of total United States crude oil production and WTI crude oil prices by studying its performance in the time-frequency domain applying wavelet tools for its resolution. Using wavelet methodologies, we observe a shift to higher frequencies of the wavelet coherency for the time period 2003–2009 and lower frequencies for the period 2009–2014. The results also indicate that during the period 2003–2009 the U.S. oil production and WTI oil prices time series are in phase; they move together, with total United States oil production leading. During the period 2009–2014 oil production and WTI oil prices time series are out of phase (negatively correlated), suggesting that oil production increases precede a decrease in WTI oil prices. In the second part of the paper and to give greater credibility to the results obtained through the wavelet transform, we analyze the behavior of WTI crude oil before and after the shale oil boom in the United States employing methodologies based on long run dependence. The results indicate that mean reversion takes place only for the data corresponding to the first subsample, ending at 2003. For the second subsample, as well as for the whole sample, lack of mean reversion is detected with orders of integration equal to or higher than 1 in all cases.

RMB Internationalization and Energy Prices: Evidence for Co-integration, Causality and Interaction Relationship

Objective:Energy pricing in the international energy market is the key point for RMB internationalization, which can make the process further developed.Aim:Therefore it is of practical significance to study their co-integration relationship and causality, and though the impulse response to analyze their dynamic interaction relationship.Method:We take the Johansen co-integration and VAR model to explore the interaction between them.Results:Empirical results show that, firstly there is a long-term equilibrium between RMB internationalization and energy prices, and the change of short-term energy prices have a positive impact on the RMB internationalization index. Secondly, WTI oil price, domestic oil price and domestic coal price linearly Granger cause the RMB internationalization, but not vice versa. While RMB internationalization is only the Granger cause of the international coal price. Finally, the impulse response analysis shows that changes of energy prices play positive roles in promoting the internationalization of RMB.

Dependence between oil price volatility, Islamic and conventional Dow Jones indexes: Implication for portfolio management and hedging effectiveness

The purpose behind this paper is twofold. Firstly, it aims at discussing the relationship between oil price and Islamic as well as conventional Dow Jones indexes. Secondly, it focuses on determining the optimal portfolio hedging strategy. In broader terms, it helps analyze the extreme dependence structure lying between oil price and Islamic as well as conventional Dow Jones indexes, using Kendall Tau estimation through copula approach. More importantly, it is designed to determine the most appropriate hedging strategy fit for oil stock portfolio against the negative variation risk predominating stock market prices. The variables involved in our research are WTI and Brent Oil Price, Islamic Dow Jones index, and conventional Dow Jones index. Using daily data relevant to the period ranging from January 1, 1996 to March 17, 2014, the study applies the FIEGARCH-EVT-Copula and Hedge ratios analysis. The reached findings have revealed that the dependence structure proves to differ noticeably among the Islamic Dow Jones – oil price and the conventional Dow Jones one. Indeed, the Islamic Dow Jones indexes appear to be more dependent on the WTI and Brent oil price than the conventional Dow Jones index. Based on the Hedging ratio and mean–variance approach, investment in Islamic index–oil portfolio has been discovered to be more beneficial as compared to investing in conventional index–oil portfolio.

U.S. stock markets and the role of real interest rates

Abstract Using weekly data from January 3, 2003 to March 27, 2015, we examine the responses of U.S. stock returns (S&P 500, DJIA, and NASDAQ) to monetary policy, controlling for WTI oil prices and the value of the U.S. dollar (USD) against major currencies. Based on differences between the federal funds rate and inflation expectations, U.S. real interest rates have become continuously negative since January 28, 2009. Vector auto-regressions (VARs) suggest stronger linkages more recently and vine copula models identify the structure of dependence across these markets, which can help investors optimize portfolio diversification.

Multivariate FIGARCH and long memory process: evidence of oil price markets

Article history: Received March 25, 2015 Received in revised format June 1 2015 Accepted June 17 2015 Available online June 22 2015 Oil price markets can benefit from a better considerate of how shocks can affect volatility through time. This study assesses the impact of structural changes and outliers on volatility persistence of two crude oil markets WTI and Brent oil price between January 1, 1996 and March 17, 2014. First, we identify the FIGARCH process proposed by Baillie et al. (1996) [Baillie, R.T., Bollerslev, T., & Mikkelsen, H.O., (1996), Fractionally integrated generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 74, 3-30.] and investigate some of its statistical proprieties and then incorporate this information into the volatility modelling. We also show that outliers can bias the estimation of the persistence of the volatility. Taking into account outliers on the volatility modelling process improve the understanding of volatility in crude oil markets. Growing Science Ltd. All rights reserved. 5 © 201

DO OIL SHOCKS DRIVE BUSINESS CYCLES? SOME U.S. AND INTERNATIONAL EVIDENCE

Oil prices rose sharply prior to the onset of the 2007–2009 recession. Hamilton [in thePalgrave Dictionary of Macroeconomics(2008)] noted that nine of the last ten recessions in the United States were preceded by a substantial increases in the price of oil. In this paper, we consider whether oil price shocks significantly increase the probability of recessions in a number of countries. Because business cycle turning points generally are not available for other countries, we estimate the turning points together with oil's effect in a Markov-switching model with time-varying transition probabilities. We find that, for most countries, oil shocks do affect the likelihood of entering a recession. In particular, for a constant, zero-term spread, an average-sized shock to WTI oil prices increases the probability of recession in the United States by nearly 50 percentage points after one year and nearly 90 percentage points after two years.

Estudio del fenómeno de inflación importada vía precios del petróleo y su aplicación al caso colombiano mediante el uso de modelos var para el periodo 2000–2009

The objective of this article is to examine whether the oil price variable fueled a phenomenon of imported inflation in Colombia for the period from January 2000 to July 2009. The estimation strategy is based on the VAR (Vector Autoregression) model taking into account WTI oil prices and the CPI (Consumer Price Index). This model provided evidence that shows that Colombia may be a case of imported inflation, signaling that inflation is not an endogenous process, but rather a process under the influence of external variables.

Modelling oil price expectations: Evidence from survey data

Using Consensus Forecast survey data on WTI oil price expectations for 3- and 12-month horizons over the period November 1989 to December 2008, we find that the rational expectation hypothesis is rejected and that none of the traditional extrapolative, regressive and adaptive processes fits the data by itself. We suggest a mixed expectation model defined as a linear combination of these traditional processes, which we interpret as the aggregation of individual mixing behavior and of heterogenous groups of agents using these simple processes. This approach is consistent with the economically rational expectations theory. We show that the target oil price included in the regressive component of this model depends on the long-run marginal cost of crude oil production and on short term macroeconomic fundamentals whose effects are subject to structural changes. For the two horizons, estimation results provide evidence for our mixed expectation model incorporating this break-dependent target price.

Extreme Movements and Measuring Risk in WTI Oil Prices

We investigate the performance of Value at Risk (VaR) models at measuring risk for WTI oil one-month futures returns. VaR models are used to calculate commodity market risk at extreme quantiles: 0.95, 0.99, 0.995 and 0.999 for both long and short trading positions. Widespread VaR models do not provide adequate risk coverage and their performance is especially weak for short position in oil. Conditional and unconditional extreme value theory VaR models are found to be the only ones correctly forecasting the true level of upside and downside risk. We also investigate the closeness of fit of theoretical distributions to the extreme tails of oil returns. Results show that generalised Pareto distribution provides the best fit to both tails of oil returns although tails differ significantly, with the right tail having a higher tail index, indicative of more extreme events.

Do Oil Shocks Drive Business Cycles? Some U.S. and International Evidence

Oil prices rose sharply prior to the onset of the 2007-2009 recession. Hamilton (2005) noted that nine of the last ten recessions in the United States were preceded by a substantial increase in the price of oil. In this paper, we consider whether oil price shocks significantly increase the probability of recessions in a number of countries. Because business cycle turning points generally are not available for other countries, we estimate the turning points together with oil’s effect in a Markov-switching model with time-varying transition probabilities. We find that, for most countries, oil shocks do affect the likelihood of entering a recession. In particular, for a constant, zero term spread, an average-sized shock to WTI oil prices increases the probability of recession in the U.S. by nearly 50 percentage points after one year and nearly 90 percentage points after two years.

Non Linear Oil Price Dynamics - A Tale of Heterogeneous Speculators?

While some of the recent surge of oil prices can be attributed to robust global demand at a time of tight production capacities, commentators occasionally also blame the impact of speculators for part of the price pressure. We propose an empirical oil market model with heterogeneous speculators. Whereas trend-extrapolating chartists may tend to destabilize the market, fundamentalists exercise a stabilizing effect on the price dynamics. Using monthly data for WTI oil prices, our STR-GARCH estimates indicate that oil price cycles may indeed emerge due to the nonlinear interplay between different trader types.

Nonlinear Oil Price Dynamics: A Tale of Heterogeneous Speculators?

While some of the recent surge of oil prices can be attributed to robust global demand at a time of tight production capacities, commentators occasionally also blame the impact of speculators for part of the price pressure. We propose an empirical oil market model with heterogeneous speculators. Whereas trend-extrapolating chartists may tend to destabilize the market, fundamentalists exercise a stabilizing effect on the price dynamics. Using monthly data for WTI oil prices, our STR-GARCH estimates indicate that oil price cycles may indeed emerge due to the nonlinear interplay between different trader types.

The New World Oil Pricing System—Year 2000

Why? Just a couple of years ago, the WTI oil price was around $10 per barrel. Much of the annual world statistical data looks fairly normal, but the crude oil price tripled. Our answer is that the petroleum industry has invited in the financial community to help set the future energy price. In the late eighties and early nineties, many “points” were established where a trader could conveniently make paper (financial) energy trades. The Industry has created futures markets, WTI at Cushing, Oklahoma, Brent at Rotterdam, Natural Gas at the Henry Hub in Louisiana. Fuel Oil and Gasoline in New York harbor. Even Electricity is traded at select points in the U.S. These crude oil futures pricing signals are mostly based on the industrialized nation’s current oil inventories, and on market psychology— but certainly not long-term supply and demand trends. Today’s paper energy traders have zero vested interests in the long-term energy future.