Crude Oil Futures as an Indicator of Market Changes: A Graphical Analysis

This study investigates the changing relationship between price and volume traded of short- and long-maturity NYMEX light sweet crude oil futures contracts and major changes in the physical crude oil market during the last decade. Monthly series for the #1-month to 84-month out maturity contracts are generated from daily price and volume data for NYMEX West Texas Intermediate (WTI) futures contracts for the period from January 2000 to the middle of 2009. 3-D graphical analysis of the futures prices, contract volumes, maturity dates, and time is used to demonstrate the changing trading volume pattern and evolution of the shape of futures price term structure across various contract maturities in different market regimes. The study observes the impacts of both May 2004, when excess production capacity reached nearly zero, and September 2006, when electronic trading was implemented on the NYMEX WTI futures markets. This analysis will be used to determine if futures contract information can provide an early indication of market regime shifts and improve short-run crude oil spot price forecast models.     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

An investigation into the dynamic relationship between international and China’s crude oil prices

This article studies the dynamic relationship between international (WTI, Brent and Dubai) and domestic (Da Qing) crude oil prices in China using threshold cointegration method. We find evidence of a long-run equilibrium relationship between each pair of international and Da Qing oil prices, favouring the market integration hypothesis. We also estimate asymmetric adjustments under the momentum threshold autoregressive (M-TAR) specification in a TVECM, and the results show that adjustments to eliminate disequilibrium happen faster when oil price spread increases than when it decreases. The long-run and short-run Granger causality tests support the notion that China has influence on the international oil markets. The results imply that China should open up its domestic and imported oil markets, and also establish a well-functioning crude oil futures market, as they are essential for arbitrage and hedging strategies.     

Risk assessment of oil price from static and dynamic modelling approaches

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.     

Forecasting realized volatility of crude oil futures with equity market uncertainty

This paper examines whether the equity market uncertainty (EMU) index contains incremental information for forecasting the realized volatility of crude oil futures. We use 5-min high-frequency transaction data for WTI crude oil futures and develop six heterogeneous autoregressive (HAR) models based on classical HAR-type models. The empirical results suggest that EMU contains more incremental information than the economic policy uncertainty (EPU) for forecasting the realized volatility of crude oil futures. More importantly, we argue that EMU is a non negligible additional predictive variable that can significantly improve the 1-day ahead predictive accuracy of all six HAR-type models, and improve the 1-week ahead forecasting performance of the HAR-RV, HAR-RV-J, HAR-RSV, HAR-RV-SJ models. These findings highlight a strong short-term and a weak mid-term predictive ability of EMU in the crude oil futures market.     

The role of financial speculation in the energy future markets: A new time-varying coefficient approach

To study whether speculating behavior plays an important role in oil futures markets, this paper proposes a time-varying coefficient version of the model of Llorente, Michaely, Saar, and Wang (2002) and estimates the effect of the speculating behavior using a sieve maximum likelihood estimation method. Using the time-varying coefficient model and the data of crude oil and heating oil futures markets, we find that neither the speculative motive nor the hedging motive dominates the markets over the whole sample period. However, we find that one of the two motives dominates the markets over some subsample periods. More importantly, speculation dominates in both the crude oil and heating oil futures markets around 2008. These empirical findings support the argument that the speculating behavior significantly affected the sharp rise in the price of crude oil in 2008.     

THE LEAD–LAG RELATION BETWEEN THE S&P500 SPOT AND FUTURES MARKETS: AN INTRADAY-DATA ANALYSIS USING A THRESHOLD REGRESSION MODEL

In this paper we examine the lead–lag interaction between the futures and spot markets of the S&P500 using the threshold regression model on intraday data. The use of threshold variables to model the changes in the regression structure with respect to different market conditions enables us to investigate the lead–lag interaction in a data-based approach and avoid stratifying the data arbitrarily. Using the basis as the threshold variable, we find that the short-selling restrictions in the spot market reduce the effect of the spot index as the leading variable. To study the effect of market-wide information on the interaction between the spot and futures markets, we use the coefficient of determination in the regression of the S&P500 on the Morgan–Stanley Composite Index-US and the Major Market Index as the threshold variable. We find that the lead effect of the futures market over the spot market is stronger when there is more market-wide information. On the other hand, the lead effect of the cash market over the futures market is weaker when there is more market-wide information. In addition, we also use the lagged 45-min return of the spot market as the threshold variable. We find that the lead effect of the spot market is stronger in periods of directionless trading than in periods of good or bad markets.     

Asset prices and expected monetary policy: evidence from daily data

This article explores the relationships among Libor, gold prices, the exchange rate, oil prices, fed funds futures prices and stock prices at a daily frequency. This article examines whether expected monetary policy, measured by changes in the prices of fed funds futures contracts, reacts to high frequency changes in asset prices and, in turn, whether asset prices respond to changes in expected monetary policy. The article reveals that there are statistically significant relationships between expected US monetary policy and shocks to Libor and exchange rates. It also reveals that there is no evidence of a systematic relationship between stock prices and expected monetary policy changes. Splitting the data into expansionary and recessionary periods using NBER dating, we find results for the expansionary periods that are very similar to the results for the entire period. For the periods of recession, we find little evidence of significant linkages between markets.     

Hedging against bunker price fluctuations using petroleum futures contracts: constant versus time-varying hedge ratios

The effectiveness of hedging marine bunker price fluctuations in Rotterdam, Singapore and Houston is examined using different crude oil and petroleum future contracts traded at the New York Mercantile Exchange (NYMEX) and the International Petroleum Exchange (IPE) in London. Using both constant and dynamic hedge ratios, it is found that in and out-of-sample hedging effectiveness is different across regional bunker markets. The most effective futures instruments for out of sample hedging of spot bunker prices in Rotterdam and Singapore are the IPE crude oil futures, while for Houston it is the gas oil futures. Differences in hedging effectiveness across regional markets are attributed to the varying regional supply and demand factors in each market. In comparison to other markets, the cross-market hedging effectiveness investigated in the bunker market is low.     

The heterogeneous dependence between global crude oil and Chinese commodity futures markets: evidence from quantile regression

This paper explores the dependence between global crude oil and Chinese commodity futures markets across different quantiles of the return distributions. Based on weekly data from 11 June 2004 to 7 July 2017, we address this issue by applying a quantile regression method. This technique provides a more detailed investigation of the dependence. Moreover, considering the structural breaks caused by market turmoil or financial crises, we divide the full period of every commodity sector market into sub-periods based on these break dates to further explore the dependence changes. The empirical results indicate that the dependence between global crude oil and Chinese commodity futures markets is different across quantiles in different commodity sectors. The dependence is significantly positive, except in markets with high expected returns. Additionally, the effects caused by structural breaks are distinctly heterogeneous across quantiles. The effect of the same break on the degree of dependence exhibits an increasing tendency as the quantile level increases, which suggests that markets with high expected returns are more susceptible to crises. Finally, we apply a prediction analysis to further verify the heterogeneity of the commodity sectors, which may be the cause of the heterogeneous dependence.     

Optimization agricultural production under financial risk of water constraint in the Jordan Valley

Using high-frequency data the co-movements among crude oil prices are analysed in order to address the question of regionalization of the world crude oil market. Time-series econometrics in the form of error-correction modelling is applied for daily crude oil price data covering the time period 1988 to 2004 and in this framework topics like weak and strong exogeneity among three major oil prices – represented by Brent, OPEC and Texas (WTI) – are addressed. The empirical results are that causality is most likely bi-directional among these crude oil prices – and hence rejecting a regionalization hypothesis of the global oil market – and also an influence from the OPEC oil price towards Bent and WTI, which are usually claimed to have a benchmark role.     

Time‐Varying Spot and Futures Oil Price Dynamics

In this paper, we investigate the role of crude oil spot and futures prices in the process of price discovery by using daily data over the period from January 1992 to September 2012. We provide evidence that futures markets play a more important role than spot markets, but their relative contributions turn out to be highly unstable, especially for the most deferred contracts. Furthermore, considering the time‐varying dynamics provides evidence of a smaller role for futures markets and a greater role for fundamental factors in driving oil prices during the global financial turmoil of 2007–2008. The implications of the main results for hedging and forecasting crude oil spot prices are also discussed.     

Volatility transmission between stock and foreign exchange markets: a connectedness analysis

ABSTRACT

This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to May 2018. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach

This paper attempts to make use of a Copula-based GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) Model to find out the relationships between the volatility of rubber futures returns in the Agricultural Futures Exchange of Thailand (AFET) and other four main markets, namely, the volatility of rubber futures returns in the Singapore Commodity Exchange (SICOM), the volatility of rubber futures returns, crude oil returns, and gas oil returns in the Tokyo Commodity Exchange (TOCOM). The results illustrate that the Student-t dependence only shows better explanatory power than the Gaussian dependence structure and the persistence pertaining to the dependence structure between rubber futures returns in AFET and oil futures returns, namely, crude oil futures returns and gas oil futures returns in TOCOM. Whereas, the Gaussian dependence shows better explanatory ability between rubber futures returns in AFET and other rubber futures returns, namely, the volatility of rubber futures in SICOM and TOCOM. For the multivariate Copula model, all the parameters between AFET and other variables are significant. Based on these results, with the liberalization of agricultural trade and the withdrawal of government support to agricultural producers, there is in many countries a new need for price discovery and even physical trading mechanisms, a need that can often be met by commodity futures exchanges. Hence, this paper recommends that the government supports the hedge mutual funds that can be invested in every commodities futures exchange in the world. It can also put the funds together that will contribute farmers to invest in each commodities futures market.     

Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets – WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.     

Revealing asymmetries in the loss function of WTI oil futures market

This paper examines behavioural aspects of the West Texas Intermediate (WTI) oil 1-month futures from 1995 to 2012. We consider that oil futures are formed based on an underlying generalised loss function with an unknown shape parameter that provides information regarding preferences. Even without observing fundamentals of WTI oil futures we can assess whether preferences lean towards a symmetric or asymmetric loss function. Our empirical evidence is robust across information sets and shows that overall loss preferences of WTI 1-month oil futures are rather optimistic and thus the underlying loss function is asymmetric. This implies that if one disregards this asymmetry the WTI oil futures should not be viewed as rational. We further provide statistical tests that allow deviations from a symmetric loss function. As part of a sensitivity analysis, and given the long span of our sample, we perform a novel analysis for detecting breakdowns in our series over time. Based on this analysis we re-examine the shape parameters of the loss function for WTI oil month futures for sub-periods. Interestingly, preferences of WTI 1-month oil futures have shifted towards optimism post 2008 period, marking the collapse of Lehman Brothers.     

Petroleum spreads and the term structure of futures prices

We employ the term structure of gasoline and heating oil prices, proxied by convenience yields, to explain the variation in the spread between the prices of gasoline and crude oil and the prices of heating oil and crude oil. We demonstrate that the marginal convenience yields in the gasoline and heating oil markets explained much of the variation in the spreads between 1986 and 1999. The evidence indicates the importance of a disaggregated treatment of the term structure of prices: the convenience yield is found to explain a substantially higher amount of the variation in the spread when it is decomposed by maturity, even after controls for seasonality and inventory levels are implemented. These findings support the notion that the futures term structure contains information beyond what can be garnered via obvious or easily available proxies of current supply and demand. The findings are also supported in an alternate specification that tests for the origins of information spillover (leadership) between the commodities: it is demonstrated that decomposed convenience yields explain a substantial portion of the volatility spillover from the gasoline and heating oil markets to the crude market.     

Correlated jumps in crude oil and gasoline during the Gulf War

This article employs a bivariate poisson jump model to investigate the relationship between the volatility of crude oil and gasoline especially during the period of the Gulf War. We find that greater jumps occurring in crude oil returns will appear in gasoline returns at the same time, but the magnitude of the co-movements in volatility falls. The covariance is relatively smaller in the Second Gulf War vs. the first conflict. The volatility of crude oil is of significantly high levels during periods of the war, yet the volatility of gasoline is not as sensitive as crude oil, particularly in the second conflict. Furthermore, the jump that occurred by the war did not lead both spot prices to a high persistent level for a long period, which fits the feature of the jump models. All these findings are important to market traders and hedging strategies.     

Multifractal detrended cross-correlations between WTI crude oil price fluctuations and investor fear gauges

This article investigates the cross-correlations between WTI crude oil prices and fear gauges using cross-correlation statistic test and multifractal detrended cross-correlation analysis. The results show that the cross-correlations between crude oil prices and three different kinds of fear gauges are multifractal. By finding the ‘crossover’, we separate the three pairs of time series into the short term and long term, and find that cross-correlations of small fluctuations are persistent in the short and long terms, cross-correlations of large fluctuations are strongly anti-persistent in the short and long terms. The relationship is useful to profit in future markets.