Search results
1 – 10 of over 22000The 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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
The paper demonstrates the implicit extent of international financial integration of Islamic stock markets in light of the global influence of oil prices.
Practical implications
The findings offer some highlights to researchers, portfolio managers and policymakers.
Originality/value
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.
Details
Keywords
Chia‐Hsing Huang and Liang‐Chun Ho
This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.
Abstract
Purpose
This paper seeks to study the impact of bio‐fuel policies on oil and food futures prices from December 6, 2004 to August 1, 2008.
Design/methodology/approach
The daily closing prices of brent crude oil, light sweet crude oil, corn, wheat, soybeans, and rough rice futures from December 6, 2004 to August 1, 2008 are used in this research. The vector error correction model is applied in order to study the impact of bio‐fuel policies on oil and agricultural futures prices.
Findings
Unit root and cointegration tests show that the brent crude oil, light sweet crude oil, wheat, corn, soybeans, and rough rice futures are stationary and have a long‐run equilibrium relationship. Granger causality tests of the four periods shows that the causality relationship between oil futures and food futures changes over time. The first period result shows many Granger causes on several variables at a 5 percent significance level. The second period has more Granger causes at the 5 percent significance level. However, the Granger causality relationships become fewer and fewer in the third and fourth period.
Originality/value
This is the first paper to study the impact of the four major bio‐fuel policies of Brazil, the European Union, and the USA.
Details
Keywords
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets.
Details
Keywords
Elisabete Neves, Vítor Oliveira, Joana Leite and Carla Henriques
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
Details
Keywords
Leo H. Chan, Chi M. Nguyen and Kam C. Chan
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…
Abstract
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.
Details
Keywords
Don N. MacDonald and Hirofumi Nishi
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…
Abstract
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.
Details
Keywords
Kofi A. Amoateng and Javad Kargar
The desire to increase investor interest in emerging markets has motivated many studies of return and risk characteristics of equity prices in these markets. Using data from…
Abstract
The desire to increase investor interest in emerging markets has motivated many studies of return and risk characteristics of equity prices in these markets. Using data from January 1999 to December 2002, we examine the dynamic relationships between oil, currency, and stock prices in the four major markets in the Middle East. Three of the four are highly correlated with the major stock markets. The potential for diversifying in Middle East markets is limited. The Egyptian and Jordanian markets, on one hand, and the Israeli and Saudi markets, on the other, are marginally integrated. While Israeli shekels significantly explain their equity prices, crude oil futures prices fairly explain oil‐rich Saudi and Egyptian equity prices. We conclude that it takes a long time for crude oil futures prices to reach equilibrium with stock prices in Israel when there is a shock to the system. However, it takes relatively a short time for crude spot oil prices and currency price to reach equilibrium with stock prices when there is a shock in the system of Saudi Arabia or Egypt. Our results suggest that, in the short and long term, investor decisions in these markets are influenced by oil and currency prices.
Details
Keywords
While numerous empirical studies have tried to model and forecast the oil price volatility over the years, such attempts using the crude oil volatility index (OVX) rarely exist…
Abstract
Purpose
While numerous empirical studies have tried to model and forecast the oil price volatility over the years, such attempts using the crude oil volatility index (OVX) rarely exist. In order to conceal this void, the purpose of this paper is to investigate whether including OVX in the realized volatility (RV) models improve the accuracy of predictions.
Design/methodology/approach
At the empirical stage, the authors employ several measures to frame the RV of crude oil futures returns. In particular, the authors use three different range-based RV estimators recommended by Parkinson (1980), Rogers and Satchell (1991) and Alizadeh et al. (2002), respectively.
Findings
The findings reveal that the information content of crude OVX helps to provide more accurate volatility predictions in comparison to the base-line RV model which contains only historical oil volatilities. Besides, the forecast encompassing test further suggests that the modified RV model (when OVX is introduced in the base-line RV model) forecast encompasses the conventional RV forecast in majority of the cases.
Practical implications
Since forecasting oil price volatility plays a vital role in portfolio optimization, derivatives pricing, optimum asset allocation decisions and risk management, the findings of this study thus carry important implications for energy economists, investors and policymakers.
Originality/value
This paper adds to the existing literature, since it is one of the initial studies to explore whether OVX is informative about the realized variance of the US oil market returns. The findings recommend that the information content of oil implied volatilities should be taken into account when modeling the US oil market volatility. In addition, range-based measures should be utilized while estimating the RV.
Details
Keywords
Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy…
Abstract
Purpose
Since crude oil is crucial to the nation's economic growth, crude oil futures are closely related to many other markets. Accurate forecasting can offer investors trustworthy guidance. Numerous studies have begun to consider creating new metrics from social networks to improve forecasting models in light of their rapid development. To improve the forecasting of crude oil futures, the authors suggest an integrated model that combines investor sentiment and attention.
Design/methodology/approach
This study first creates investor attention variables using Baidu search indices and investor sentiment variables for medium sulfur crude oil (SC) futures by collecting comments from financial forums. The authors feed the price series into the NeuralProphet model to generate a new feature set using the output subsequences and predicted values. Next, the authors use the CatBoost model to extract additional features from the new feature set and perform multi-step predictions. Finally, the authors explain the model using Shapley additive explanations (SHAP) values and examine the direction and magnitude of each variable's influence.
Findings
The authors conduct forecasting experiments for SC futures one, two and three days in advance to evaluate the effectiveness of the proposed model. The empirical results show that the model is a reliable and effective tool for predicting, and including investor sentiment and attention variables in the model enhances its predictive power.
Research limitations/implications
The data analyzed in this paper span from 2018 through 2022, and the forecast objectives only apply to futures prices for those years. If the authors alter the sample data, the experimental process must be repeated, and the outcomes will differ. Additionally, because crude oil has financial characteristics, its price is influenced by various external circumstances, including global epidemics and adjustments in political and economic policies. Future studies could consider these factors in models to forecast crude oil futures price volatility.
Practical implications
In conclusion, the proposed integrated model provides effective multistep forecasts for SC futures, and the findings will offer crucial practical guidance for policymakers and investors. This study also considers other relevant markets, such as stocks and exchange rates, to increase the forecast precision of the model. Furthermore, the model proposed in this paper, which combines investor factors, confirms the predictive ability of investor sentiment. Regulators can utilize these findings to improve their ability to predict market risks based on changes in investor sentiment. Future research can improve predictive effectiveness by considering the inclusion of macro events and further model optimization. Additionally, this model can be adapted to forecast other financial markets, such as stock markets and other futures products.
Originality/value
The authors propose a novel integrated model that considers investor factors to enhance the accuracy of crude oil futures forecasting. This method can also be applied to other financial markets to improve their forecasting efficiency.
Details