Oil Spot Prices Research Articles

Exchange rates, oil prices and electricity spot prices: empirical insights from European Union markets

This study investigates the relationship between daily electricity spot price returns and both the crude oil spot price return (in US dollars) and the exchange rate return in six European countries (France, Germany, Italy, the Netherlands, Spain and the United Kingdom) during the time periods 2005-7 and 2008-11, ie, before and after the contagion of the subprime crisis on European markets. The conditional mean and conditional variance are modeled by AR(1)-GARCH(1,1) and AR(1)-NGARCH(1,1). The performance superiority of the nonlinear asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) model suggests that the leverage effect is well represented. In many cases, the level of returns in either the oil price or the exchange rate had little impact on the level of electricity price returns, but the volatility of these prices affected the volatility of electricity prices in all the European countries examined, except for the United Kingdom. However, in the succeeding time period (2008-11), the volatility of electricity prices in each of the countries studied, including the United Kingdom, was significantly and asymmetrically affected by both exchange rate and oil price returns. This volatility, or risk, has implications for the way in which low-carbon generators should be supported.

The Relevance of Future Contracts on Spot Price Formation in Crude Oil Markets

This paper aims to examine the role different future contracts play on oil spot price formation. Firstly the cointegration and causality hypothesis are tested using appropriate methodologies. Several distributed lag models are estimated in order to forecast spot price behavior, taking into account current information on future price. The results provide evidence of strong predictive power for certain short-term future contracts, using as reference the corresponding expiry date at the time of the transaction. All data have been obtained from daily quotations of the Brent and WTI crude oil prices, in US$ per barrel, in the spot market and their four nearest future contracts. The time period of the analysis spanned from June 2009 to March 2013.

Measuring the effect of oil prices on wheat futures prices

This research lends insight into the empirical validity of reverse regressions hypothesizing that spot prices today help to predict forward rates in the future. This paper analyzes the possible relationship between wheat futures prices and spot oil prices considering the importance of the effects of temporal aggregation and alternative model specification for the understanding of the empirical relationships between the two markets.Evidence indicates that model specification and time series aggregation over daily, weekly and monthly aggregations influence standard errors on parameter estimates as standard errors are likely to increase with aggregation. Therefore, t-ratios are likely to change as well. Further, while goodness-of-fit measures might increase with aggregation, forecast accuracy with macro-level aggregations might deteriorate owing to information loss. The results indicate the presence of contemporaneous causality between the variables of interest, however, the presence of strict causality is mixed and the results do vary with units of time aggregation.

Retail and Wholesale Gasoline Price Adjustments in Response to Oil Price Changes

This research examines the long-run relationship between the spot oil price and retail and wholesale gasoline prices. Recent research suggests that the response of the retail gasoline price is faster and the size of the change is larger, in magnitude, following a crude oil price increase compared with periods when the crude oil price is falling; however, some recent papers examining potential asymmetries present mixed results. Our results from a common threshold model estimating the adjustment of gasoline prices and the spot oil price suggest a long-run relationship between retail and wholesale gasoline prices and the crude oil price. Further, results here suggest that both retail and wholesale gasoline prices respond symmetrically to an oil price shock in the long run, indicating little market power by gas stations and wholesalers.

Crude Oil Spot Price Forecasting Based on Multiple Crude Oil Markets and Timeframes

This study proposes a multiple kernel learning (MKL)-based regression model for crude oil spot price forecasting and trading. We used a well-known trend-following technical analysis indicator, the moving average convergence and divergence (MACD) indicator, for extracting features from original spot prices. Additionally, we factored in the possibility that movements of target crude oil prices may be related to other important crude oil markets besides the target market for the prediction time horizon since traders may find price movement information within other relevant crude oil markets useful. We also considered multiple timeframes in this study since trends may differ across different timeframes and, in fact, traders may use their own timeframes. Therefore, for forecasting target crude oil prices, this study emphasizes on features pertaining to other important crude oil markets and different timeframes in addition to features of the target crude oil market and target timeframe. Moreover, the MKL framework has been used to fuse information extracted from different sources and timeframes of the same data source. Experimental results show that out-of-sample forecasting using the MKL method is superior to benchmark methods in terms of root mean square error (RMSE) and average percentage profit (APP). They also show that the information from multiple timeframes is useful for prediction, but that from another crude oil market is not.

The relationship between oil prices and stock prices: a nonlinear asymmetric cointegration approach

This article investigates the long-run and short-run dynamics between US stock prices and oil prices over the period from 1 January 1992 to 22 November 2013 using the S&P 500 index and West Texas Intermediate spot oil prices. Unlike the majority of previous studies that are based on the conventional time series analysis, we examine for the presence of different sources of nonlinearities, such as structural breaks and asymmetric adjustments in the dynamic links between the investigated markets. The results from the threshold autoregressive (TAR) and momentum threshold autoregressive (MTAR) models of Enders and Siklos (2001) in conjunction with the Threshold Error Correction Model estimations provide evidence of asymmetric responses towards the equilibrium.

Extreme dependence between China’s oil market and the world oil market: empirical evidence and implications

In recent years, China’s increasing dependence on oil imports has raised major concerns about energy security and risk management. This paper examines China’s extreme dependence on the global market using time-varying copulas. Using the sample of Daqing (China), West Texas Intermediate (United States), Brent (North Sea), Dubai (Middle East) and Minas (Asia-Pacific) spot oil prices, we find that the dynamic conditional correlation (DCC) Student t copula can more properly describe the dependence between China’s and the global oil market. It indicates that negative and positive extreme results between China’s and the global oil markets are linked with the same intensity. Moreover, for the Daqing–Brent and Daqing–Dubai pairs, there have been significant increases in extreme dependencies in recent years. Among the three subperiods during 2007–11, their extreme dependencies rose more sharply in periods of global economic recession and global economic recovery than in times of global economic boom. For China’s oil investors and energy policy makers, the empirical findings may have important implications for developing hedging strategies and energy pricing.

Analysis of the Behavior of Volatility in Crude Oil Price

This article analyzes volatility in the spot price of crude oil. In recent years the price has also increased reaching more than US$ 140/barrel in the last decade. Moreover, the negotiated trading volume in the futures market in recent years higher than the trading volume of the earlier years. How these changes have affected the volatility in the oil prices? Does the presence of huge players, which leads to an increase in the volume under negotiation, increase volatility? Has the persistence been affected? To answer these questions, we first estimated spot prices using the two-factor model of Schwartz and Smith. With this filtering process we can capture the entire information from the future term-structure. We then analyzed the estimated spot-price series to identify the stylized facts and then adjusted conditional volatility models of GARCH family. Our findings show that the volatility in the high prices period is not different from that of low prices. The shocks behaved as transitory and the persistence in the high prices period decreased. This fact has pricing and hedging implications for short-term derivatives.

FORECASTING CRUDE OIL PRICE MOVEMENTS WITH OIL‐SENSITIVE STOCKS

This paper uses monthly data from 1984:M10 to 2012:M8 to show that oil‐sensitive stock price indices, particularly those in the energy sector, have strong power in predicting nominal and real crude oil prices at short horizons (1‐month‐ahead predictions), using both in‐ and out‐of‐sample tests. In particular, the forecasts based on oil‐sensitive stock price indices are able to outperform significantly the no‐change forecasts. For example, using the NYSE Arca (AMEX) oil index as a predictor, the 1‐month‐ahead forecasts for nominal crude oil prices reduce the mean squared prediction error by between 22% (for the West Texas Intermediate oil price) and 28% (for the Dubai oil price). Moreover, we find that the directional forecast based on the AMEX oil index is significantly better than a 50:50 coin toss. The novelty of this analysis is that it proposes a new and valuable predictor that both reflects timely market information and is readily available for forecasting the spot oil price.(JEL G17, Q43, Q47, C53)

Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model

A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS). The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI) and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.

Time‐Varying Spot and Futures Oil Price Dynamics

AbstractIn 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.

The Rise of Shale Gas and Russia's Countermeasures

The recent expansion of shale gas development in the US has been greatly contributing to the drop in natural gas prices in the country, and to job growth and enhanced competitiveness in relevant manufacturing areas such as the petrochemical industry. Since the first half of 2009, the US natural gas spot price (Henry Hub), unlike the crude oil (WTI) spot price (Cushing Hub), has been showing a steady downward trend. Lowered gas prices have been serving as cause for cost cuts in gas production, the petrochemical industry, the primary metal industry and so forth, and this is helping improve price competitiveness in the US manufacturing sector. Spot price decoupling between crude oil and natural gas has led to a change in the energy mix, with natural gas enjoying higher consumption.

Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks

This paper uses monthly data from 1984:M10 to 2012:M8 to show that oil-sensitive stock price indices, particularly those in the energy sector, have strong power in predicting nominal and real crude oil prices at short horizons (one-month-ahead predictions), using both in- and out-of-sample tests. In particular, the forecasts based on oil-sensitive stock price indices are able to outperform significantly the no-change forecasts. For example, using the NYSE Arca (AMEX) oil index as a predictor, the one-month-ahead forecasts for nominal crude oil prices reduce the mean squared prediction error by between 22% (for the West Texas Intermediate oil price) and 28% (for the Dubai oil price). Moreover, we find that the directional forecast based the AMEX oil index is significantly better than a 50:50 coin toss. The novelty of this analysis is that it proposes a new and valuable predictor that both reflects timely market information and is readily available for forecasting the spot oil price.

Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices

An accurate prediction of crude oil prices over long future horizons is challenging and of great interest to governments, enterprises, and investors. This paper proposes a revised hybrid model built upon empirical mode decomposition (EMD) based on the feed-forward neural network (FNN) modeling framework incorporating the slope-based method (SBM), which is capable of capturing the complex dynamic of crude oil prices. Three commonly used multi-step-ahead prediction strategies proposed in the literature, including iterated strategy, direct strategy, and MIMO (multiple-input multiple-output) strategy, are examined and compared, and practical considerations for the selection of a prediction strategy for multi-step-ahead forecasting relating to crude oil prices are identified. The weekly data from the WTI (West Texas Intermediate) crude oil spot price are used to compare the performance of the alternative models under the EMD–SBM–FNN modeling framework with selected counterparts. The quantitative and comprehensive assessments are performed on the basis of prediction accuracy and computational cost. The results obtained in this study indicate that the proposed EMD–SBM–FNN model using the MIMO strategy is the best in terms of prediction accuracy with accredited computational load.

The Role Of Oil Speculation On The Economy: The Problem With The View Of Fattouth, Kilian, And Mahadeva

On July 30, 2012, Fattouth, Kilian, and Mahadeva published and online paper titled, The Role of Oil Speculation in Oil Markets: What Have We Learned So Far? They concluded that the existing evidence is not supportive of an important role of speculation in driving the spot price of oil after 2003. This paper aims to show that the conclusion of their paper, which challenges the finding of direct correlation between oil speculation and rising spot oil prices in Ajuzie et al. (published in 2009) is fraught with omissions that have led to mistaken conclusions. In their literature review, they failed to include opposing findings, even when those views are in public domain. Because of the enormous negative consequences that will result from misapplication of economic policies based on such mistaken conclusions, it is important to address the error in their finding.

The Role of Speculation in Oil Markets: What Have We Learned So Far?

A popular view is that the surge in the real price of oil during 2003-08 cannot be explained by economic fundamentals, but was caused by the increased financialization of oil futures markets, which in turn allowed speculation to become a major determinant of the spot price of oil. This interpretation has been driving policy efforts to tighten the regulation of oil derivatives markets. This survey reviews the evidence supporting this view. We identify six strands in the literature and discuss to what extent each sheds light on the role of speculation. We find that the existing evidence is not supportive of an important role of speculation in driving the spot price of oil after 2003. Instead, there is strong evidence that the co-movement between spot and futures prices reflects common economic fundamentals rather than the financialization of oil futures markets.

An Empirical Investigation of Volatility of Indian Spot and Future Prices of Crude Oil

Recent volatility in crude oil prices has affected economies around the world. The paper is focused towards empirically testing the significance in volatility of the spot prices due to future prices of oil commodity in India. The study also investigates the dynamic relationship between both the price series. These interactions, in tum, give rise to publicly reported futures prices that reflect the market's best estimate today of what future supply and demand conditions and, hence, prices will be. The objectives of the study are examined by employing Chow test to check structural break points in prices data, ADF test to check the stationarity, Johansen's co-integration test for examining the long term relationship, and Garch (1, 1) model to check the volatility in spot and the future prices of crude oil. The daily closing data is taken from 1st May 2005 to 31st December 2012 for the analysis. Since the period of financial crisis is considered, the entire period (May 2005‐ December 2012) is divided into three sub-periods, namely before crisis period (May 2005‐ August 2008), during crisis (September 2008‐ December 2010) and after crisis period Oanuary 2011‐ December 2012). The findings of the study proved that there are structural break points in the specified data and the series derived from the futures prices and cash market prices for crude oil were not stationary in the level form, but there is evidence of stationarity in the first difference form. Long run relationship between the spot and future price series is also observed. Empirical results also found that in the period during crisis and after crisis there is persistence of high volatility. However, the period before crisis shows less volatility than the other two periods.

The fundamental and speculative components of the oil spot price: a real option value approach

This paper investigates the recent evolution of the oil price, with the objective to analyze the main drivers that during last fifteen years have led the unstable path and the volatility persistence in the international oil market. We assume that the oil price is composed by two components, deterministic and speculative. The first one can be defined as the certain one, and it is referred to the fundamental component given by supply and demand interaction. Differently, the uncertain one is given by unclear changes in the price structure, and it is assumed to be linked to the speculative activity. Through a structural equation model (SEM) in a linear reduced form we find that the speculation in the oil market measured with the real option methodology can improve the traditional model explaining a consistent part of the oil fluctuations.

Leverage vs. Feedback: Which Effect Drives the Oil Market?

This article brings new insights on the role played by (implied) volatility on the WTI crude oil spot price. An increase in the volatility subsequent to an increase in the oil price (i.e. inverse leverage effect) remains the dominant effect as it might reflect the fear of oil consumers to face rising oil prices. However, this effect is amplified by an increase in the oil price subsequent to an increase in the volatility (i.e. inverse feedback effect) with a two-day delayed effect. This lead-lag relation between the oil price and its volatility is determinant for any type of trading strategy based on futures and options on the OVX implied volatility index, and thus is of interest to traders, risk- and fund-managers.

Reconnoitering the Causal Relationship in Crude Oil Market during Crisis

The purpose of this paper is to study in Indian context (during the recent US financial crisis period), whether there is significant impact of Crude Oil future trading on crude spot prices or there is no such impact. We examine the effect of futures trading volume of crude oil to crude oil spot prices in the Multi Commodity Exchange of India (MCX) from January 2007 until Dec 2009. The vector autoregressive model (VAR), Granger Causality Wald test, Variance Decomposition and Impulse Response Function are applied to the data collected. The results exhibited that bidirectional causality runs from crude spot prices to futures trading volume.