Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests

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.

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GDP, energy consumption and financial development in Italy

International Journal of Energy Sector Management ◽

10.1108/ijesm-01-2017-0004 ◽

2018 ◽

Vol 12 (1) ◽

pp. 28-43 ◽

Cited By ~ 18

Author(s):

Cosimo Magazzino

Keyword(s):

Energy Consumption ◽

Granger Causality ◽

Financial Development ◽

Oil Prices ◽

Content Type ◽

Real Gdp ◽

Long Run ◽

Causality Tests ◽

Granger Causality Tests ◽

Toda And Yamamoto

Purpose This study aims to explore the relationship among energy consumption, real income, financial development and oil prices in Italy over the period 1960-2014. Design/methodology/approach Different econometric techniques – such as the General Methods of Moment (GMM) or the AutoRegressive Distributed Lags (ARDL) bounds test – are usually used in the empirical analysis. Moreover, both the Toda and Yamamoto causality tests and the Granger causality tests are applied to the data. Findings The results of unit root and stationarity tests show that the variables are non-stationary at levels, but stationary in first-differences form, or I(1). The ARDL bounds F-test reveals an evidence of a long-run relationship among the four variables at 1% significance level. Moreover, an increase in real GDP and oil prices has a significant effect on energy consumption in the long run. The coefficients of estimated error correction term are also negative and statistically significant. In addition, the paper explores the causal relationship between the variables by using a VAR framework, with Toda and Yamamoto but also Granger causality tests, within both multivariate and bivariate systems. The findings indicate that energy consumption is affected by real GDP. Originality/value The study also filled the literature gap of applying ARDL technique to examine this relevant issue for Italy.

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Oil Prices and Economic Growth in Major Emerging Economies

Applied Econometric Analysis - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-7998-1093-3.ch001 ◽

2020 ◽

pp. 1-23

Author(s):

Emrah I Cevik ◽

Sel Dibooglu ◽

Tugba Kantarci ◽

Hande Caliskan

Keyword(s):

Crude Oil ◽

Emerging Economies ◽

Economic Activity ◽

Oil Prices ◽

Energy Prices ◽

Empirical Results ◽

Crude Oil Prices ◽

Causality Tests ◽

The Difference ◽

The Relationship

There is a strong correlation between energy prices and economic activity. The relationship particularly holds true for crude oil as changes in oil prices are associated with changes in production costs, and economic activity also generates significant demand for energy and crude oil. This chapter examines the relationship between economic activity and crude oil prices using causality tests in the frequency domain and taking into account the difference between positive and negative changes in both oil prices and economic activity as the relationship can be asymmetric. The authors present empirical results for major emerging economies including Brazil, Russia, India, China, South Africa, and Turkey. Empirical results indicate that for most countries there is bidirectional causality between crude oil prices and economic activity whereas only negative oil price shocks seem to negatively affect economic activity.

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Time-Varying Granger Causality Tests for Applications in Global Crude Oil Markets: A Study on the DCC-MGARCH Hong Test

SSRN Electronic Journal ◽

10.2139/ssrn.3941778 ◽

2021 ◽

Author(s):

Massimiliano Caporin ◽

Michele Costola

Keyword(s):

Crude Oil ◽

Granger Causality ◽

Time Varying ◽

Oil Markets ◽

Causality Tests ◽

Granger Causality Tests

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Nonlinear Causality between Crude Oil Prices and Exchange Rates: Evidence and Forecasting

Energies ◽

10.3390/en14196043 ◽

2021 ◽

Vol 14 (19) ◽

pp. 6043

Author(s):

Witold Orzeszko

Keyword(s):

Exchange Rates ◽

Crude Oil ◽

Oil Prices ◽

Support Vector ◽

Time Series Modeling ◽

Crude Oil Prices ◽

Linear Framework ◽

Modeling And Forecasting ◽

Causality Tests ◽

Policy Analysts

The relationships between crude oil prices and exchange rates have always been of interest to academics and policy analysts. There are theoretical transmission channels that justify such links; however, the empirical evidence is not clear. Most of the studies on causal relationships in this area have been restricted to a linear framework, which can omit important properties of the investigated dependencies that could be exploited for forecasting purposes. Based on the nonlinear Granger causality tests, we found strong bidirectional causal relations between crude oil prices and two currency pairs: EUR/USD, GBP/USD, and weaker between crude oil prices and JPY/USD. We showed that the significance of these relations has changed in recent years. We also made an attempt to find an effective strategy to forecast crude oil prices using the investigated exchange rates as regressors and vice versa. To this aim, we applied Support Vector Regression (SVR)—the machine learning method of time series modeling and forecasting.

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

Information Science and Management Engineering II (Set) ◽

10.2495/isme20142352 ◽

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

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The co-movement and asymmetry between energy and grain prices: Evidence from the crude oil and corn markets

Energies ◽

10.3390/en12071373 ◽

2019 ◽

Vol 12 (7) ◽

pp. 1373 ◽

Cited By ~ 2

Author(s):

Chen ◽

Wang ◽

Zhang ◽

Zheng

Keyword(s):

Crude Oil ◽

Granger Causality ◽

Price Change ◽

Oil Price ◽

Oil Market ◽

Non Linear ◽

Causality Tests ◽

Causality Relationship ◽

Granger Causality Tests ◽

Grain Prices

This paper investigates the co-movement and asymmetric interactions between energy and grain prices, based on the evidence from the crude oil and corn markets, the most important energy and grain markets, respectively. Time series analysis indicates that there is a consistent trend between the crude oil price and corn price with a significant positive correlation coefficient 0.7471 during the sampling period, from January 2008 to February 2016. In addition, we find that there is a long-run equilibrium relationship between the two commodities’ prices. Moreover, while linear Granger causality tests suggest that there is a two-way Granger causality relationship between the price changes in the two markets, non-linear Granger causality tests suggest that there is only a one-way causality relationship from corn to oil price. However, both linear and non-linear Granger causality tests indicate the asymmetry of causality relationship between the two markets (the price change in corn market can more significantly Granger cause the change in crude oil market). Further analysis suggests that the contribution of the corn market to price discovery in a large commodity market is larger than that of the crude oil market.

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How does investor attention affect international crude oil prices?

Applied Energy ◽

10.1016/j.apenergy.2017.07.131 ◽

2017 ◽

Vol 205 ◽

pp. 336-344 ◽

Cited By ~ 25

Author(s):

Ting Yao ◽

Yue-Jun Zhang ◽

Chao-Qun Ma

Keyword(s):

Crude Oil ◽

Oil Prices ◽

Investor Attention ◽

Crude Oil Prices

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Grain prices, oil prices, and multiple smooth breaks in a VAR

Studies in Nonlinear Dynamics & Econometrics ◽

10.1515/snde-2014-0101 ◽

2016 ◽

Vol 20 (4) ◽

Cited By ~ 21

Author(s):

Walter Enders ◽

Paul Jones

Keyword(s):

Structural Change ◽

Granger Causality ◽

Null Hypothesis ◽

Structural Breaks ◽

Oil Prices ◽

Misspecified Model ◽

Causality Tests ◽

Granger Causality Tests ◽

The Relationship ◽

Smooth Breaks

AbstractIgnored structural breaks in a VAR result in a misspecified model such that Granger causality tests are improperly sized; there is a bias towards a rejection of the null hypothesis of non-causality even when the null is correct. Instead of modeling structural breaks as being sharp, changes in the relationship between the maize and petroleum markets are likely to have occurred gradually. We show the flexible Fourier form has good size and power properties in testing for smooth structural change in a VAR. When applied to a VAR including maize and oil prices, we uncover important linkages between the two markets.

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