Research on relationships between crude oil prices and offshore equipment manufacturing industry based on Granger causality test

2014 ◽  
Author(s):  
Xiaoyan Ge
Keyword(s):  
Crude Oil ◽  
Granger Causality ◽  
Manufacturing Industry ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Causality Test ◽  
Crude Oil Prices ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry

scholarly journals Do Tense Geopolitical Factors Drive Crude Oil Prices?

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4277
Author(s):  
Fen Li ◽  
Zhehao Huang ◽  
Junhao Zhong ◽  
Khaldoon Albitar
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Causal Link ◽  
Short Term ◽  
Causality Test ◽  
Dynamic Correlation ◽  
Crude Oil Prices ◽  
Political Events ◽  
Real Factor ◽  
Copula Approach

Geopolitical factors are considered a crucial factor that makes a difference in crude oil prices. Over the last three decades, many political events occurred frequently, causing short-term fluctuations in crude oil prices. This paper aims to examine the dynamic correlation and causal link between geopolitical factors and crude oil prices based on data from June 1987 to February 2020. By using a time-varying copula approach, it is shown that the correlation between geopolitical factors and crude oil prices is strong during periods of political tensions. The GPA (geopolitical acts) index, as the real factor, drives the rise in prices of crude oil. Moreover, the dynamic correlation between geopolitical factors and crude oil prices shows strong volatility over time during periods of political tensions. We also found unidirectional causality running from geopolitical factors to crude oil prices by using the Granger causality test.

Dynamic linkages among international crude oil, exchange rate and Norwegian stock market: evidence from ARDL bound testing approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shelly Singhal ◽  
Sangita Choudhary ◽  
Pratap Chandra Biswal
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Oil Price ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Integration Test

Purpose The purpose of this paper is to examine the long-run association and short-run causality among oil price, exchange rate and stock market in Norwegian context. Design/methodology/approach This work uses auto regressive distributed lag (ARDL) bound co-integration test to examine the long-run association among international crude oil, exchange rate and Norwegian stock market. Further to test the causality, Toda–Yamamoto Granger causality test is used. Daily data ranging from 1 January, 2011 to 31 December, 2018 is used in this study. Findings Findings of this study suggest the existence of long-run equilibrium relationship among oil price, exchange rate and Norwegian stock market when oil price is taken as dependent variable. Further, this study observes the bi-directional causality between Norwegian stock market and exchange rate and unidirectional causality between oil and Norwegian stock market (from oil to stock market). Originality/value To the best of the authors’ knowledge, this the first study in context of Norway to explore the long-run association and causal relationships among international crude oil price, exchange rate and stock market index. Particularly, association of exchange rate and stock market largely remains unexplored for Norwegian economy. Further, majority of studies conducted in Norwegian setup have considered the period up to year 2010 and association of these variables is found to be time varying. Finally, this study uses ARDL bound co-integration test and Toda–Yamamoto Granger causality test. These methodologies have been used in literature in context of other countries like India and Mexico but not yet applied to study the Norwegian case.

The dynamic information spill-over effect of WTI crude oil prices on China’s traditional energy sectors

2018 ◽  
Vol 10 (3) ◽  
pp. 516-534 ◽  
Author(s):  
Yue-Jun Zhang ◽  
Yao-Bin Wu
Keyword(s):  
Crude Oil ◽  
Stock Returns ◽  
Oil Prices ◽  
Petroleum Processing ◽  
Time Varying ◽  
Causality Test ◽  
Content Type ◽  
Market Values ◽  
Crude Oil Prices ◽  
Linear And Nonlinear

PurposeThe purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.Design/methodology/approachHong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.FindingsThe empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.Originality/valueThe general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.

scholarly journals Modeling Nonlinear Granger Causality and Co-Integration Between Gold Price Returns and Crude Oil Price Returns

2018 ◽  
Vol 14 (2) ◽  
pp. 105-116
Author(s):  
Nawaz Ahmad ◽  
Keyword(s):  
Crude Oil ◽  
Granger Causality ◽  
Oil Prices ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Long Run ◽  
Gold Market ◽  
Oil Markets ◽  
Causality Tests ◽  
Multiplicative Effects

To model the nonlinear analysis of commodities, Gold market and crude oil market have importance to test their lead and lag price mechanism between the two. For this purpose, the log transformation has been done to calculate easier multiplicative effects. However, to record the dynamic effects of long run cointegreation model applied and tested to find the significance of the problem statement issues. Furthermore, granger causality approach also uses to examine the fundamental linkages between Gold Prices and Crude Oil prices. Meanwhile, the study of Gold markets and oil markets gained popularity among development economists during in last some decades. And try to find out stochastic relationship between the two nonlinear markets. The academic practitioners paved their efforts to run casual time series models in order to find out the robust results which help the economists and financial experts to drive the industry indicator in positive way. This study confirmed that there is cointegration between the two important indicators of large market commodities i.e Gold and crude oil and also casual interactions. Pairwise Granger Causality Tests concluded that Gold Prices return has Granger Cause on Oil Prices return in the long run and if the βeta change in the prices of gold may affect on the prices of crude oil in the long run.

Do Macroeconomic Variables Impact the Indian Stock Market?

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Khalid Ul Islam ◽  
Mohsina Habib
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Causal Relationship ◽  
Granger Causality ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Indian Stock Market

This paper is intended to study the impact of various macroeconomic variables on Indian stock market. Based on the Arbitrage Pricing Theory (APT) propounded by Ross in 1976 and various other studies, a number of macroeconomic variables including, inflation, industrial production, exchange rate, money supply, interest rate, and oil price have been identified to have a significant impact on the stock market. We have applied the multivariate extension of the classical linear regression model computed on Ordinary Least Squares method and Granger Causality test to re-establish the relationship between macroeconomic variables and stock returns over a period of 10 years from 2005 to 2015 using monthly observations. The results of this study show that only exchange rate has a significant negative impact on stock returns. The other macroeconomic variables are not significantly affecting stock returns, however, their impact is in accordance with the economic theory. The Granger Causality test reveals absence of any causal relationship between stock returns and macroeconomic variables, except in case of oil prices, where we find a unidirectional causal relationship running from stock returns to oil prices. However, the Granger Causality results should not be taken in the conventional meaning of causality, but results merely identifying precedence.

scholarly journals Modelling Technological Progress Evaluation: Case of Lithuanian Manufacturing Industry

2020 ◽  
Vol 11 (6) ◽  
pp. 1
Author(s):  
Mantas Markauskas ◽  
Asta Baliute
Keyword(s):  
Granger Causality ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Spillover Effect ◽  
Granger Causality Test ◽  
Var Model ◽  
Var Models ◽  
Causality Test ◽  
Technological Spillover ◽  
Error Terms

The goal for this research is to build a framework for analysis of technological spillover effect between sectors in Lithuanian manufacturing industry and assess whether predictors of the created model closely follow dynamic fluctuations of technological progress assessed values. Analysis of academic literature suggested using Granger causality test and vector autoregression (VAR) model to analyze intersectoral technological progress spillover effect in any manufacturing industry. Granger causality test can suggest a potential relationship between technological progress values of particular sectors in manufacturing industry while VAR model can define the exact form and extent of spillover effect. VAR models identify presence of intersectoral technological spillover effect in case of 15 out of 18 sectors in Lithuanian manufacturing industry. In case of a few sectors error terms of VAR models are not stationary suggesting that additional exogenous variables need to be included to increase accuracy of estimated coefficients before these models can be used in further analysis. After minor changes presented VAR models can be used for sensitivity analysis analyzing how changes in different sectoral level parameters affect economic development of manufacturing industry as a whole.

scholarly journals To Assess the Association between Exchange Rate, Commodity Prices and Cryptocurrency in Indonesia

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Nur Hussain
Keyword(s):  
Exchange Rate ◽  
Granger Causality ◽  
Commodity Prices ◽  
Oil Prices ◽  
Granger Causality Test ◽  
Oil Price ◽  
The Other ◽  
Causality Test ◽  
Cotton Price ◽  
Crypto Currency

The paper aimed to assess the association among exchange rate, commodity prices and crypto currency in Indonesia. This study is quantitative in which the data has been gathered from the Investing.com from 2016 to 2020. The variables which were considered in the study include exchange rate, gold prices, cotton prices, oil prices, Bitcoin and Ethereum. In terms of the analysis, the vector autoregression and granger causality test has been adopted.The results of this study identified that there is no effect of exchange rate, oil price, cotton price and gold price on Bitcoin. On the other hand, there is only significant effect of gold prices on Ethereum. The results of this study are restricted to Indonesian context and the data has been considered from 2016 to 2019 due to the lack of data on crypto currency.

scholarly journals The Linkages between Crude Oil and Food Prices

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6545 ◽  
Author(s):  
Monika Roman ◽  
Aleksandra Górecka ◽  
Joanna Domagała
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Food Prices ◽  
Food Price ◽  
Price Transmission ◽  
Data Series ◽  
Food Groups ◽  
Causality Test ◽  
Crude Oil Prices ◽  
The Impact

This paper aims to indicate the linkages between crude oil prices and selected food price indexes (dairy, meat, oils, cereals, and sugar) and provide an empirical specification of the direction of the impact. This paper reviews the fuel–food price linkage models with consideration to the time series literature. This study adopts several methods, namely the Augmented Dickey–Fuller test, Granger causality test, the cointegration test, the vector autoregression model, and the vector error correction model, for studying the price transmission among the crude oil and five selected food groups. The data series covers the period between January 1990 and September 2020. The empirical results from the paper indicate that there are long-term relationships between crude oil and meat prices. The linkage of crude oil prices occurred with food, cereal, and oil prices in the short term. Furthermore, the linkages between the analyzed variables increased in 2006–2020.

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