scholarly journals An Auxiliary Index for Reducing Brent Crude Investment Risk—Evaluating the Price Relationships between Brent Crude and Commodities

2021 ◽  
Vol 13 (9) ◽  
pp. 5050
Author(s):  
Yu-Wei Chen ◽  
Chui-Yu Chiu ◽  
Mu-Chun Hsiao
Keyword(s):  
New York ◽  
Crude Oil ◽  
Oil Price ◽  
Spot Price ◽  
Investment Risk ◽  
Crude Oil Price ◽  
Price Relationship ◽  
Heating Oil ◽  
Price Relationships ◽  
Practical Measurement

Examining the price relationships of Brent Crude with 78 global commodities, our study shows that the spot price of a certain commodity, New York Harbor No. 2 Heating Oil Spot Price FOB, can serve as an auxiliary forecasting index of the rise and fall of the monthly Brent Crude oil price. With an innovative view for evaluating the price relationship and prediction based on simple, practical measurement, our findings provide a helpful auxiliary index tool for investors and analysts by offering a high success rate (82.98%) and predicting the rise and fall of the monthly Brent Crude oil price three weeks in advance.

The Co-Movements Between Crude Oil Price and Internet Concerns: Causality Analysis in the Frequency Domain

2020 ◽  
Vol 8 (3) ◽  
pp. 224-239
Author(s):  
Jingjing Li ◽  
Ling Tang ◽  
Ling Li
Keyword(s):  
Crude Oil ◽  
Test Method ◽  
Oil Price ◽  
Spot Price ◽  
Causality Analysis ◽  
Crude Oil Price ◽  
Causality Test ◽  
Low Frequencies ◽  
Oil Market

AbstractWith the boom of web technology, Internet concerns (IC) have become emerging drivers of crude oil price. This paper makes the first attempt to measure the frequency-varying co-movements between crude oil price and IC in five domains (i.e., fundamentals, supply-demand, crisis, war and weather) by using the frequency causality test method. Based on the monthly Brent spot price and search volumes (SVs) captured by Google Trends from January 2004 to September 2019, new and complementary insights regarding the co-movements between crude oil price and IC are obtained. 1) The co-movements between crude oil price and the IC of supply-demand, war, and weather support a neutral hypothesis at all frequencies due to the characteristics (low value or volatility) of these IC data. 2) There is a unidirectional causal relationship between crude oil price and the IC of fundamentals, running from the latter to the former at low frequencies (long-term). 3) There is a feedback relationship between crude oil price and the IC of crisis, with the IC of crisis driving crude oil price at medium and low frequencies (mid- and long-term) and crude oil price causing the IC of crisis to change permanently. The conclusions of this paper provide important implications for both oil market economists and investors.

Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships

2012 ◽  
Vol 34 (5) ◽  
pp. 1507-1513 ◽  
Author(s):  
Islam Hassouneh ◽  
Teresa Serra ◽  
Barry K. Goodwin ◽  
José M. Gil
Keyword(s):  
Crude Oil ◽  
Sunflower Oil ◽  
Parametric Modeling ◽  
Oil Price ◽  
Crude Oil Price ◽  
Price Relationships ◽  
Non Parametric

scholarly journals Unveiling the Effect of Mean and Volatility Spillover between the United States Economic Policy Uncertainty and WTI Crude Oil Price

2020 ◽  
Vol 12 (16) ◽  
pp. 6662
Author(s):  
Ruixin Su ◽  
Jianguo Du ◽  
Fakhar Shahzad ◽  
Xingle Long
Keyword(s):  
Economic Policy ◽  
Crude Oil ◽  
The United States ◽  
Oil Price ◽  
Var Model ◽  
Spot Price ◽  
Policy Uncertainty ◽  
Volatility Spillover ◽  
Crude Oil Price ◽  
The Us

Grounded in the Granger causality test, vector autoregression (VAR) model, and BEKK-GARCH model, our current study aims to examine the effect of mean and volatility spillover between the United States (US) economic policy uncertainty (EPU) and West Texas Intermediate (WTI) crude oil price. Using the US EPU monthly index and WTI spot price data from 1996 to 2019, we revealed that there is a one-way Granger causality link between the US EPU and spot price of WTI crude oil. The VAR model not only illustrated that there is a mean spillover effect between WTI oil price and US EPU, but they will also be affected by its memory, as well as the other’s past. At the same time, it also pointed out that this correlation has positive and negative directions. The BEKK-GARCH model test yielded similar conclusions to the VAR model and, importantly, proved a two-way volatility spillover effect between the US EPU and WTI spot price fluctuations. In conclusion, US economic policy has a substantial influence on the variation of global crude oil prices, as an essential strategic reserve resource and will also influence the government’s economic policy formulation. Understanding the association between WTI crude oil price and policy uncertainty not only helps investors to manage assets allocations and mitigate losses but also guides US policymakers to adjust the energy structure for economic sustainability.

scholarly journals Forecasting Volatility of Crude oil Prices using Box-Jenkins's Autoregressive Moving Average: Evidence from Indian Chemical Industry

2019 ◽  
Vol 8 (3) ◽  
pp. 229-234
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Oil Prices ◽  
Information Criteria ◽  
Oil Price ◽  
Spot Price ◽  
Autoregressive Moving Average ◽  
Crude Oil Price ◽  
Oil Companies ◽  
Crude Oil Prices

The current paper deals with to forecast volatility in crude oil prices in Indian economy. In the current study volatility is measured through change in monthly crude oil prices per barrel. The monthly data of crude oil price have taken from January 1995 to May, 2017. The different unit root tests are applied to test check change in crude oil price series is stationary or non stationary. Box-Jenkins's Autoregressive Moving Average of Box-Jenkins methodology has been used for developing a forecasting model. Minimum Akaike Information Criteria (AIC) has been opted to arrive at fit good ARMA model. According to this criteria (4, 3)(0,0) was observed as one of the best model to predict the volatility in future crude oil prices. Forecasted volatility in prices may be utilized for calculating future spot price and hedging future risk. Moreover, forecasted prices volatility of crude oil will also beneficial to oil companies, policy makers for formulating different economic policies and taking some crucial economic decision.

scholarly journals Food versus crude oil: what do prices tell us? Evidence from China

2015 ◽  
Vol 7 (3) ◽  
pp. 435-447 ◽  
Author(s):  
Yumeng Wang ◽  
Shuoli Zhao ◽  
Zhihai Yang ◽  
Donald J. Liu
Keyword(s):  
Crude Oil ◽  
Error Correction ◽  
Food Prices ◽  
Oil Price ◽  
Price Transmission ◽  
Crude Oil Price ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
Price Relationship

Purpose – The purpose of this paper is to investigate the causal relationship between the prices of rice, crude oil, wheat, corn and soybean in China and estimate the long-run and short-run price relationships. Design/methodology/approach – Using monthly price date over the period of January 1998-December 2013 in China, this paper employs an autoregressive distributed lag (ARDL) bounds test to explore the cointegration relationship among the price variables and estimate the ARDL long-run price relationship and the short-run error correction process (ARDL-EC). Findings – The empirical results indicate that crude oil, as one of the forcing variables along with wheat, corn, and soybean prices, is effecting rice price in China. Both the long-run and short-run price transmission elasticity estimates suggest the importance of crude oil price on the formation of rice prices. Furthermore, the adjustment speed coefficient is found to be statistically significant, supporting the notion that there is an error correction mechanism for maintaining the long-run price relationship facing short-run shocks. Originality/value – This paper adopts four types of commodity food prices to explore the relationships with crude oil price. The evidence of market integration, including the degree of price transmission and the speed of adjustment, remains a crucial step to proceed with the government intervention.

scholarly journals Sugeno Intuitionistic Fuzzy Generator Based Computational Technique for Crude Oil Price Forecasting

2020 ◽  
Vol 5 (3) ◽  
pp. 488-496
Author(s):  
Gunjan Goyal ◽  
Dinesh C. S. Bisht
Keyword(s):  
Time Series ◽  
Crude Oil ◽  
Fuzzy Sets ◽  
Time Series Forecasting ◽  
Oil Price ◽  
Fuzzy Time Series ◽  
Spot Price ◽  
Computational Technique ◽  
Crude Oil Price ◽  
Intuitionistic Fuzzy

Crude oil being a significant source of energy, change of crude oil price can affect the global economy. In this paper, a new approach based on the intuitionistic fuzzy set theory has been implemented to predict the crude oil price. This paper presents the intuitionistic fuzzy time series forecasting algorithm to enhance the efficacy of time series forecasting which includes fuzzy c-means clustering to obtain the optimal cluster centers. Further, a computational technique is proposed for the construction of triangular fuzzy sets and these fuzzy sets are converted to intuitionistic fuzzy sets with the help of Sugeno type intuitionistic fuzzy generator. The popular benchmark dataset of West Texas Intermediate crude oil spot price is used for the validation process. The numerical results when compared with existing methods notify that the proposed method enhances the accuracy of the crude oil price forecasts.

Impact of crude oil price on the socio-political environment of global countries

2019 ◽  
Vol 118 (3) ◽  
pp. 110-122
Author(s):  
Johnson Clement Madathil ◽  
Velmurugan P. S
Keyword(s):  
Crude Oil ◽  
Descriptive Analysis ◽  
Oil Price ◽  
Policy Framework ◽  
Political Environment ◽  
Policy Reforms ◽  
Crude Oil Price ◽  
Short Term ◽  
Political Impact ◽  
New Energy

Crude oil is known to have an impact on people’s life of both producers and consumers of crude oil countries. A producer country’s socio-political impact will be different from a consumer country’s socio-political impact. This paper aims to show that crude oil price has a socio-political impact on global countries through descriptive analysis. The study found that there were similarities in the movement of crude oil price and change in GDP of both India and United States and further Russia and Venezuela have had crude oil impact on their respective GDP’s, which has made them take policy reforms. The paper identifies changes in the policy framework due to influence of crude oil price and eventual changes in existing socio-political environment. Taking oil producing countries such as Russia and Venezuela as examples, this paper suggests that policy reforms are the key to having a stable socio-political environment. Russia shows us that having a flexible monetary policy can keep the budget dependence on crude oil reduced in the short term. On the other hand, for oil consuming countries, having a stable supply and moving to new energy sources is the key to tackle the influence of crude oil price on the socio-political environment of global countries.

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