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This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.

With daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.

The empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.

The MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.

The purpose of this paper is to investigate the global influence of crude and refined oil futures prices on Dow Jones Islamic equity indices (DJIMI) during the recent global financial crisis under structural breaks in the conditional volatility of oil futures prices.

It aims at exploring the long-run and the short-run elasticity and causal relationships using an ARDL bound testing approach and a vector error correction model.

The main findings confirm the presence of long-run relationship for DJIM emerging markets index compared to other global and sub-regional developed indexes. Speed of adjustment to the long-run equilibrium is moderate and the effect of structural breaks, produced from nonlinear volatility model with long memory (LM), is overall not pronounced for that relationship. Short-run causality is bi-directional but long-run Granger causality does not run from refined oil to the DJIMI and crude oil.

The paper demonstrates the implicit extent of international financial integration of Islamic stock markets in light of the global influence of oil prices.

The findings offer some highlights to researchers, portfolio managers and policymakers.

The paper gives an answer to an identified need to test the position of Islamic equity markets as booming Islamic investment and socially responsible investment areas to the global influence of the new soaring path of oil markets. It uses as well bounds testing approach and tests weak and strong causalities under structural breaks. It considers as well LM behavior in oil prices along with the asymmetry property in oil prices.

The purpose of this paper is to study the efficiency of different oil and gas markets. Most previous studies examined the issue using low frequency date sampled at monthly, weekly, or daily frequencies. In this study, 30-minute intraday data are used to explore efficiency in energy markets.

Sophisticated statistical analysis techniques such as Granger-causality regressions, augmented Dickey-Fuller tests, cointegration tests, vector autoregressions are used to explore the transmission of information between oil and gas energy markets.

This study provides evidence for efficiency in energy markets. The new information that arrives either to futures markets or spot markets is digested correctly, completely, and in a fast manner, and is propagated to the other market. The evidence indicates high efficiency.

This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets.

This paper aims to examine dynamic equicorrelations (DECO) and directional volatility spillover effects among four energy futures markets, namely, West Texas Intermediate crude oil, heating oil, natural gas and reformulated blendstock for oxygenate blending gasoline, by using a multivariate fractionally integrated asymmetric power ARCH–DECO–generalized autoregressive conditional heteroskedasticity (GARCH) model and the spillover index technique.

The empirical analysis uses the dynamic equicorrelation model of Engle and Kelly (2012) to examine time-varying correlations at equilibrium. The authors further analyze dynamic volatility transmission among energy futures by using Diebold and Yilmaz (2012) dynamic spillover index based on generalized value-at-risk framework.

The empirical results provide evidence of heightened equicorrelations at times of financial turmoil. More specifically, the dynamic spillover analysis shows that volatility is transmitted predominantly from crude oil to the other markets and risk transfer among four markets exhibits asymmetries. Spillovers are found to be highly responsive to dramatic events such as the 9/11 terror attack, 2008–2009 global financial crisis and 2014–2016 oil glut.

The results of this study have important practical implications for investors, portfolio managers and energy policymakers as the presence of time-varying co-movements and spillovers suggests the need for dynamic trading strategies. There are also implications regarding risk management practices, as there is evidence of increased volatility transmission at times of financial turmoil and uncertainty. Finally, the results provide insights to policymakers in a better understanding of the spillover dynamics.

This paper investigates the DECOs and spillover effects among crude oil, natural gas, heating oil and gasoline futures markets. To the best of the knowledge, this is one of a few studies that examine co-movements and risk transfer in energy futures in a comprehensive framework.

In this chapter, we apply the new measure of speculative activities (hereafter, named the speculative ratio) in Chan, Nguyen, and Chan (2013) to study the relationship between those activities and volatility in the oil futures market. We document that the speculative ratio (trading volume divided by open interest) can isolate speculative elements from total trading activities. Using the oil futures data and dividing the data into two subperiods surrounding Hurricane Katrina, we find an increased speculative trades in the post-Hurricane Katrina period. Our results show that speculative activities create a more volatile oil futures market and they lower the information flow between volatility and speculative activities in the post-Hurricane Katrina period.

The purpose of this paper is to examine the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets. In so doing, the paper addresses two important issues. First, whether there is a positive relationship between returns and trading volume in the crude oil futures markets. Second, whether information regarding trading volume contributes to forecasting the magnitude of return in the markets, an important issue because the ability of trading volume to predict returns imply market inefficiency.

The paper used daily closing futures price and their corresponding trading volumes for WTI and Brent crude oil markets during the sample period January 2008 to May 2011. Both the log volume and the unexpected component of the detrended volume are used in the analysis in other to have robust alternative conclusion. The generalized method of moments (GMM) approach is used to examine the contemporaneous relationship between returns and trading volume while the Granger causality approach, impulse response and variance decomposition analysis are used to investigate the ability of trading volume to predict returns in the oil futures markets.

The results reject the postulation of a positive relationship between trading volume and returns, suggesting that trading volume and returns are not driven by the same information flow which contradicts the mixture of distribution hypothesis in all markets. The results also show that neither trading volume nor returns have the power to predict the other and therefore contradicting the sequential arrival hypothesis and noise trader model in all markets. Finally, the findings support the weak form efficient market hypothesis in the crude oil futures markets.

The findings has important implications to market regulators because daily price movement and trading volume do not respond to the same information flow and therefore the measures that control price volatility should not focused more on volume; otherwise they may not provide fruitful outcomes. Additionally, traders and investors who participate in oil futures should not base their decisions on past trading volume because it will lead to profit loss. The results also have implications for market efficiency as past information cannot assist speculators to forecast returns in all the oil markets. Finally, investors can benefit from portfolio diversification across the two markets.

This chapter develops a no-arbitrage, futures equilibrium cost-of-carry model to demonstrate that the existence of cointegration between spot and futures prices in the New York Mercantile Exchange (NYMEX) crude oil market depends crucially on the time-series properties of the underlying model. In marked contrast to previous studies, the futures equilibrium model utilizes information contained in both the quality delivery option and convenience yield as a timing delivery option in the NYMEX contract. Econometric tests of the speculative efficiency hypothesis (also termed the “unbiasedness hypothesis”) are developed and common tests of this hypothesis examined. The empirical results overwhelming support the hypotheses that the NYMEX future price is an unbiased predictor of future spot prices and that no-arbitrage opportunities are available. The results also demonstrate why common tests of the speculative efficiency hypothesis and simple arbitrage models often reject one or both of these hypotheses.

This paper aims to better understand if speculative activity is a factor or even the main factor in the run-up of oil prices in the spot market, particularly in the recent price bubble that occurred in the period from mid-2003 to 2008.

The methodology used is based on an existing vector autoregressive model proposed by Kilian and Murphy (2014), which is a structural model of the global market for crude oil that accounts for flow demand and flow supply shocks and speculative demand oil shocks.

From the output of the authors’ structural model, the authors ruled out speculation as a factor of rising oil prices. The authors have found instead that the rapid oil demand caused by an unexpected increase in the global business cycle is the most accurate culprit. Despite the change of perspective in the speculative component, the authors’ conclusions concur with the findings of Kilian and Murphy (2014) and others.

As far as the authors are aware, this is the first time that a study has used as a spread oil variable, a speculative component of the real price, replacing the oil inventories considered by Kilian and Murphy (2014). Another contribution is that the model used allows estimating traditional oil demand elasticity in production and oil supply elasticity in spread movements, casting doubt on existing models with perfect price-inelastic output for crude oil.

This paper aims to provide an important perspective to the predictive capacity of Organization of the Petroleum Exporting Countries (OPEC) meeting dates and production announcements for energy futures (crude oil West Texas Intermediate (WTI), gasoline reformulated gasoline blendstock for oxygen blending (RBOB), Brent oil, London gas oil, natural gas and heating oil) market returns and volatilities.

To examine the impact of OPEC news on energy futures market returns and volatilities, the authors use a conditional quantile regression methodology during the period from April 01, 2013 to June 30, 2017.

From the empirical findings, the authors show a conditional dependence between energy futures returns and OPEC-based predictors; hence, the authors can find clear the significance of relationship in the process of financialization of the OPEC announcements and energy futures in the case of this paper. From the quantile-causality test, the authors find that the effect of OPEC news is important to energy futures. Specifically, OPEC announcements dates predict the quantiles of the conditional distribution of energy futures market returns.

The authors confirm the presence of unidirectional nexus between OPEC news and energy commodities futures in the long term.