Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests

Using the Google search volume index (GSVI) to measure investor attention, this paper investigates the relationships between investor attention and crude oil prices for the main crude oil markets worldwide. To account for possible structural breaks and nonlinearity in the relation between investor attention and oil returns, Fourier unit root test and nonlinear Granger causality tests are employed. The empirical results suggest that the bidirectional nonlinear Granger causality exists only between investor attention and WTI future crude oil return. However, WTI crude oil return Granger-causes investor attention weakly. For Dubai spot, Daqing spot, WTI spot and Brent future oil markets, unidirectional nonlinear Granger causality runs from investor attention to oil returns, which is relatively weak.     

Extreme risk spillovers between crude oil and stock markets

This paper investigates the spillovers of extreme risks between crude oil and stock markets using daily data of the S&P 500 stock index and West Texas Intermediate (WTI) crude oil futures returns. Based on the method of Granger causality in risk, Value at Risk (VaR) is employed to measure market risk, and a class of kernel-based tests is used to detect negative and positive risk spillover effects. Empirical results reveal that there are significant risk spillovers between the two markets. Extreme movements, past or current, in one market may have a significant predictive power for those in the other market. Prior to the recent financial crisis, there are positive risk spillovers from stock market to crude oil market, and negative spillovers from crude oil market to stock market. After the financial crisis, bidirectional positive risk spillovers are strengthened markedly. The risk spillovers may occur instantaneously, and/or with a (long) time delay. Both positive and negative risk spillover effects exhibit asymmetric correlations.     

Crude oil shocks and stock markets: A panel threshold cointegration approach

This paper proposes a panel threshold cointegration approach to investigate the relationship between crude oil shocks and stock markets for the OECD and non-OECD panel from January 1995 to December 2009. Nonlinear cointegration is confirmed for the oil–stock nexus in the panel. Because threshold cointegration is found, the threshold vector error correction models can be run to investigate the presence of asymmetric dynamic adjustment. The Granger causality tests demonstrate the existence of bidirectional long-run Granger causality between crude oil shocks and stock markets for these OECD and non-OECD countries. However, the short-run Granger causality between them is bidirectional under positive changes in the deviation and unidirectional under negative ones. Moreover, the speed of adjustment toward equilibrium is faster under negative changes in the deviation than that under positive ones in these OECD and non-OECD countries.     

Analyzing time-varying volatility spillovers between the crude oil markets using a new method

The spillover effect is an important factor affecting the volatility of crude oil price. Basing on the study of Diebold and Yilmaz (2009, 2012, 2014), we propose a new method that calculates the time-varying volatility spillover indexes by the generalized forecast error variance decomposition of TVP-VAR-SV model. Then, using the new method, we study the time-varying volatility spillovers between four major crude oil markets (WTI, Brent, Oman, Tapis) from November 29, 2002 to July 13, 2018. By comparing the results of our new method and traditional rolling window method, we verify the superiority of our new method. The results show that the volatility spillovers calculated by the new method are clearer, more stable and not outlier sensitive. From the estimated results of time-varying volatility spillovers, we find that the volatility spillover between crude oil markets is slowly increasing, but there are obvious cyclical changes. And from the correlation analysis and the Granger causality test, we find that the volatility and volatility spillovers are positively correlated and are two-way Granger causality, which supported for the market infection hypothesis of King and Wadhwani (1990).     

Wavelet-based test of co-movement and causality between oil and renewable energy stock prices

We studied co-movement and causality between oil and renewable energy stock prices using continuous and discrete wavelets, firstly, to obtain information on dynamic correlations over time and for different time scales from wavelet coherence and, secondly, to obtain information on linear and non-linear Granger causality in the time-frequency domain. For general and sectoral renewable energy indices for the period 2006–2015, our findings indicate that dependence between oil and renewable energy returns in the short run was weak but gradually strengthened towards the long run, mainly for the period 2008–2012. Our causality tests provide evidence against linear causality at higher frequencies and in favour of unidirectional and bidirectional linear causality at lower frequencies. In contrast, we found consistent evidence of non-linear causality running from renewable energy indices to oil prices at different time horizons and mixed evidence of causality running from oil to renewable energy prices. These results have potential implications for investors in terms of hedging and for policymakers in terms of policy support decisions regarding the development of renewable energy.     

Estimating ‘Value at Risk’ of crude oil price and its spillover effect using the GED-GARCH approach

Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets.     

Interaction among China carbon emission trading markets: Nonlinear Granger causality and time-varying effect

China makes great efforts to reduce carbon emissions and mitigate global greenhouse gas. In order to identify the interaction among China CET markets, this paper comprehensively investigates nonlinear Granger causality and time-varying effect in markets by using the Hiemstra and Jones (HJ) test, Diks and Panchenko (DP) test and time-varying parameter structure vector autoregressive (TVP-SVAR) model. The empirical analysis has demonstrated China major CET markets significantly bidirectional nonlinear Granger cause each other. As to time-varying effect, we have obtained convincing findings that time-varying impulse responses are among China major CET markets in the short term. Specifically, Guangdong, Hubei and Shenzhen CET markets are time-varying co-movement, negatively or positively related to each other over time, implying there are deep bases for China national CET market construction. Furthermore, the specific time point impulse effects support our discoveries in time-varying impulse responses.     

Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies

We provide novel insight to the emerging literature on the role of U.S. monetary policy as a driver of a global financial cycle by examining the possible causal effect of U.S. economic policy uncertainty on the connectedness of crude oil and currency markets, using a sample of commodity currencies from advanced and emerging nations. A battery of linear and nonlinear Granger-based causality tests indicate the presence of a causal relationship between economic policy uncertainty and the connectedness of oil and currency markets, particularly at low frequencies and more significantly after the outburst of the global financial crisis. While crude oil generally serves as a net transmitter of shocks to currencies across all frequency bands, the spillover effects from oil are largely concentrated towards the G10 currencies of Australian and New Zealand dollar that are often used as investment currencies in global carry trade strategies. Overall, our findings suggest the presence of a significant pass-through effect of economic policy uncertainty via oil prices, spilling over to the currency market, in line with the emerging evidence that the monetary policy by the U.S. Fed serves as a major driver of a global financial cycle that describes patterns in global capital flows, credit activity and asset prices across financial markets.     

Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis

This study explores the dynamic co-movement between oil and six stock markets (China, India, Japan, Saudi Arabia, Russia, and Canada) by using two types of wavelet analysis (wavelet multi-scale decomposition and wavelet coherence). The main empirical results are as follows: (1) Maximal overlap discrete wavelet transform analysis shows that there are feedback relationships between the price movement of oil and stock markets in all six countries in the wavelet-based decomposition at the D₄, D₅, and D₆ scales. (2) The pairs of oil and stock returns show high overall co-movement at the 16- to 128-week scale based on continuous wavelet transform analysis. The wavelet coherence and phase plots show that the pairs of oil and oil-importing stock market returns have high co-movement for the period between 2007 and 2012 (especially during the global financial crisis of 2008). In addition, the wavelet coherence and phase plots show that the pairs of oil and oil-exporting stock market returns have high co-movement from 2007 to 2017. (3) Oil price returns lead the stock returns of Saudi Arabia, Russia and Canada from 2007 to 2017 at the 16- to 128-week scale. The stock prices are more influenced by oil prices in oil-exporting countries than in oil-importing countries. This evidence implies that the economic structure of oil-exporting countries depends strongly on crude oil production. (4) From the results of the wavelet-based Granger causality test, there is a lead-lag causality linkage in which the oil price leads stock market indices from 27 to 30 weeks (189–210 days). The implications of these findings are discussed.     

Moments-based spillovers across gold and oil markets

In this paper, we use intraday futures market data on gold and oil to compute returns, realized volatility, volatility jumps, realized skewness and realized kurtosis. Using these daily metrics associated with two markets over the period of December 2, 1997 to May 26, 2017, we conduct linear, nonparametric, and time-varying (rolling) tests of causality, with the latter two approaches motivated due to the existence of nonlinearity and structural breaks. While, there is hardly any evidence of spillovers between the returns of these two markets, strong evidence of bidirectional causality is detected for realized volatility, which seems to be resulting from volatility jumps. Evidence of spillovers are also detected for the crash risk variables, i.e., realized skewness, and for realized kurtosis as well, with the effect on the latter being relatively stronger. Based on a moments-based test of causality, evidence of co-volatility is deduced, whereby we find that extreme positive and negative returns of gold and oil tend to drive the volatilities in these markets. In our robustness check, we identify a causal chain in the realized volatility from oil to gold via the financial stress. Our results have important implications for not only investors, but also policymakers.     

Price discovery in energy markets

In this study, we empirically analyze the price discovery process in the futures and spot markets for crude oil, heating oil and natural gas using daily closing prices. We use two different information share measures that are based on the methods proposed by Gonzalo and Granger (1995) and Lien and Shrestha (2014). Both measures indicate that almost all the price discovery takes place in the futures markets for the heating oil and natural gas. However, for the crude oil, the price discovery takes place both in the futures and spot markets. As a whole, our study indicates that futures markets play an important role in the price discovery process.     

Oil market uncertainty and international business cycle dynamics

This paper sets out to identify the dynamic relationship between oil market uncertainty and international business cycle. Firstly, we implement the Granger causality linear tests and document significant linear causal relation. Then we perform the nonlinear tests, which, on the contrary, do not exhibit significant evidence of nonlinear relation between oil market uncertainty and the business cycle indicators. Further we perform the dynamic panel analysis utilizing the Arellano-Bond GMM procedure and find that oil volatility risk premium (VRP) has a significant leading effect on the output growth even controlling for country specific characters and other classic pricing factors of stock markets. Further, the impulse responses indicate that the shock of innovation in oil market uncertainty can boost the output growth within half a year and this effect will be absorbed gradually over time. Overall, oil market uncertainty does have a linear leading effect on the international business cycle.     

Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis

This paper assesses factors that potentially influence the volatility of crude oil prices and the possible linkage between this volatility and agricultural commodity markets. Stochastic volatility models are applied to weekly crude oil, corn, and wheat futures prices from November 1998 to January 2009. Model parameters are estimated using Bayesian Markov Chain Monte Carlo methods. Speculation, scalping, and petroleum inventories are found to be important in explaining the volatility of crude oil prices. Several properties of crude oil price dynamics are established, including mean-reversion, an asymmetry between returns and volatility, volatility clustering, and infrequent compound jumps. We find evidence of volatility spillover among crude oil, corn, and wheat markets after the fall of 2006. This can be largely explained by tightened interdependence between crude oil and these commodity markets induced by ethanol production.     

Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test

This paper utilizes the newly developed method of a generalized spectral test to examine the weak-form efficiency of the main worldwide crude oil markets. The generalized spectral test, unlike other methods, can detect both linear and nonlinear serial dependence in the conditional mean and allows for different forms of unknown conditional heteroscedasticity. By using a “rolling sample” approach instead of an analysis of different time periods, we find that the efficiency of oil markets may depend on time periods. The main global crude oil markets reach weak-form efficiency in the long-term and the degree of efficiency of global oil markets changes over time. Among the oil markets examined in this study, the Brent and the WTI oil markets possess the highest efficiency levels, whereas the Daqing oil market has the lowest efficiency level. Apparent anti-synchronization is detected between the efficiency of Brent and WTI markets in recent years, whereas synchronization is found between the efficiency of Daqing and Dubai oil markets during the last decade.     

Volatility spillover from world oil spot markets to aggregate and electricity stock index returns in Turkey

This study examines the inter-temporal links between world oil prices, ISE 100 and ISE electricity index returns unadjusted and adjusted for market effects. The traditional approaches could not detect a causal relationship running from oil returns to any of the stock returns. However, when we examine the causality using Cheung–Ng approach we discover that world oil prices Granger cause electricity index and adjusted electricity index returns in variance, but not the aggregate market index returns. Hence, our results show that the Cheung–Ng procedure with the use of disaggregated stock index returns can uncover new information that went unnoticed with the traditional causality tests using aggregated market indices.     

Dynamic spillover effects among crude oil,precious metal,and agricultural commodity futures markets

This paper examines spillover effects among six commodity futures markets – gold, silver, West Texas Intermediate crude oil, corn, wheat, and rice – by employing the multivariate DECO-GARCH model and the spillover index. Specifically, we investigate the dynamics of return and volatility spillover indices to reveal the intensity and direction of transmission during the recent global financial and European sovereign debt crises. Our empirical results are as follows. First, we estimate a positive equicorrelation between commodity futures market returns and find that it increased sharply during the crises. This effect can persist during periods of economic and financial turmoil, diminishing the benefits of international portfolio diversification for investors. Second, we identify bidirectional return and volatility spillovers across commodity futures markets, and find more pronounced trends in their levels in the post-crisis period. This indicates the strong impact of spillovers during crisis periods. Third, both gold and silver are information transmitters to other commodity futures markets, while the remaining four commodity futures investigated were receivers of spillovers during recent periods of financial stress. Finally, we analyse the optimal portfolio weights and time-varying hedge ratios between metal and other commodities futures markets. Overall, our findings provide new insights into channels of information transmission, which may improve investment decisions and inform portfolio investors' trading strategies.     

Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1

We examine the frequency domain connectedness among international crude oil and agriculture commodities, covering the period of 1990M1-2017M5. The frequency domain connectedness is examined at three frequencies, which roughly correspond to one to six months, six to twelve months, and a period of more than twelve months. We also use a network based on pairwise correlations and a net directional matrix generated from the frequency domain spillover method. We show that the vegetable oils are the most influential price volatility source for the other agriculture commodities, such as dairy, cereals, meat and sugar, but also for the crude oil. In addition, we find a bi-directional and asymmetric connectedness between oil and agriculture commodity markets at all different frequency bands. These findings validate the preliminary results we obtain using a rolling-based bootstrap time-varying Granger causality analysis but provide additional insights as they allow to see the direction and the strength of the volatility at different frequencies. Our findings provide novel information about the production cost channel describing the relationship between oil and agriculture commodity markets. In addition, from the financialization perspective, our results show that agriculture commodity may provide portfolio diversification benefits especially in the short run.     

Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy

This paper examines the volatility connectedness between crud oil spot prices and cryptocurrencies. Given that cryptocurrency markets are perceived as commodity markets, there exist some levels of effects from and to other markets like the crude oil (petroleum) market. Using the VAR − MGARCH − GJR − BEKK techniques and the Wald tests, we found evidence of bidirectional volatility spillover between the crude oil market and Bit Capital Vendor as well as a unidirectional volatility spillover effect from crude oil market to Bitcoin Cash market and finally, Ethereum, XRP, and ReddCoin cryptocurrency markets have a significant unidirectional volatility spillover to the crude oil markets. In addition, while the hedging potentials of crude oil assets on Ethereum cryptocurrency may be short-lived, the crude oil asset hedging potentials for Solve, Elastos and Bit Capital Vendor are rather long-lived into the future.     

Multiscale lead-lag relationships in oil and refined product return dynamics: A symbolic wavelet transfer entropy approach

This study sheds new light on the lead-lag relationships between crude oil and refined product return dynamics in the time and the frequency space. For this purpose, a novel methodology is introduced. Based on information theoretic measures and continuous wavelet transform, symbolic wavelet transfer entropy detects non-linear lead-lag relationships in the sense of Granger causality across multiple scales. Between petroleum prices, we find bidirectional causalities across the investment horizons. Further evidence is provided for asymmetric price transmission amongst crude oil and the refined products with respect to increasing and decreasing petroleum prices. Across the analyses, we observe that product price dynamics, economic crises, geopolitical risks, natural catastrophes and other market perturbations affect the price discovery in heterogenous investment horizons.     

Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India

While several studies have examined the linear causal relationship between oil prices and exchange rates, little is known about the nonlinear causality between these two variables. The present paper tries to fill this research gap in the context of India and China. By applying the Hiemstra and Jones (1994) nonlinear Granger causality test to the VAR residuals, the study finds a significant bi-directional nonlinear Granger causality between oil prices and exchange rates in both countries. The findings suggest that the nonlinearity of oil price influences the exchange rate irrespective of the exchange rate regimes. Further, to check robustness, the persistence in the variance of oil price and exchange rate is taken into account using a GARCH (1, 1) model. While the results consistently hold in the case of India, with respect to China, a unidirectional causality runs from exchange rate to oil price. However, the oil price in China does not Granger cause exchange rate.