scholarly journals Bubbles in Crude Oil and Commodity Energy Index: New Evidence

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6648
Author(s):  
Christos Floros ◽  
Georgios Galyfianakis
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Energy Index ◽  
West Texas ◽  
Crude Oil Prices ◽  
Augmented Dickey Fuller ◽  
New Evidence

This paper considers a long dataset of both Brent and West Texas Intermediate (WTI) crude oil prices and the Commodity (fuel) energy index (CEI) to identify possible bubbles. Using the Supremum Augmented Dickey–Fuller (SADF) test, we compare results from WTI and Brent with CEI. We prove that the CEI follows Brent crude oil (they provide similar bubble periods) and that Brent is recognized as a crude oil benchmark. Financial managers should incorporate it into their analysis and forecasts. The findings are strongly recommended to energy policymakers and investors.

Dynamic Relationship between Crude Oil and Stock Prices in India: Before And After the Subprime Financial Crisis 2008

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 96-104
Author(s):  
P. Sakthivel ◽  
S. Rajaswaminathan ◽  
R. Renuka ◽  
N. R.Vembu
Keyword(s):  
Financial Crisis ◽  
Crude Oil ◽  
Stock Prices ◽  
Oil Prices ◽  
Energy Index ◽  
Data Set ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run ◽  
Before And After

This paper empirically discovered the inter-linkages between stock and crude oil prices before and after the subprime financial crisis 2008 by using Johansan co-integration and Granger causality techniques to explore both long and short- run relationships.  The whole data set of Nifty index, Nifty energy index, BSE Sensex, BSE energy index and oil prices are divided into two periods; before crisis (from February 15, 2005 to December31, 2007) and after crisis (from January 1, 2008 to December 31, 2018) are collected and analyzed. The results discovered that there is one-way causal relationship from crude oil prices to Nifty index, Nifty energy index, BSE Sensex and BSE energy index but not other way around in both periods. However, a bidirectional causality relationship between BSE Energy index and crude oil prices during post subprime financial crisis 2008. The co-integration results suggested that the absence of long run relationship between crude oil prices and market indices of BSE Sensex, BSE energy index, Nifty index and Nifty energy index before and after subprime financial crisis 2008.

An empirical model of daily highs and lows of West Texas Intermediate crude oil prices

2010 ◽  
Vol 32 (6) ◽  
pp. 1499-1506 ◽  
Author(s):  
Angela W.W. He ◽  
Jerry T.K. Kwok ◽  
Alan T.K. Wan
Keyword(s):  
Crude Oil ◽  
Empirical Model ◽  
Oil Prices ◽  
West Texas ◽  
Crude Oil Prices

scholarly journals Modelling the Nigeria Crude Oil Prices Using ARIMA, Pre-intervention and Post-intervention Model

2019 ◽  
pp. 1-12
Author(s):  
Wiri, Leneenadogo ◽  
Tuaneh, Godwin Lebari
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Oil Prices ◽  
Information Criterion ◽  
Intervention Model ◽  
Post Intervention ◽  
Autoregressive Integrated Moving Average ◽  
Crude Oil Prices ◽  
Augmented Dickey Fuller ◽  
Time Plot

The study applied Autoregressive Integrated Moving Average Intervention in modelling crude oil prices in Nigeria spanning the period from January 1986 to June 2017. The time plot of the series showed an abrupt increase in the series and this called for intervention modelling. The data was divided into three set (actual series, pre-intervention and post-intervention series). The Augmented Dickey Fuller (ADF) was used to test for unit root on each of the series and were all found to be non-stationary at levels, they (actual, pre and post- intervention series) were however non stationary at first difference. Eighteen models were estimated and the best model was the pre-intervention model that minimise the Akaike information criterion (AIC) (ARIMA (111)) with AIC of (4.4.578). The plot of the residual correlogram showed adequacy of the model. The model was adequate since there was no spike that cut the level of the correlogram and the histogram of the residual was normally distributed with probability values (0.0000).

scholarly journals Dynamic Connectedness of International Crude Oil Prices: The Diebold–Yilmaz Approach

2018 ◽  
Vol 10 (9) ◽  
pp. 3298 ◽  
Author(s):  
Xiaoyong Xiao ◽  
Jing Huang
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Risk Measurement ◽  
Time Varying ◽  
Measurement Framework ◽  
West Texas ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Network Connectedness ◽  
Market Shocks

Connectedness is the key to modern risk measurement and management. This study investigates the international connectedness of crude oil prices and explores its time-varying characteristics based on a connectedness measurement framework using daily international crude oil prices. The international connectedness of crude oil prices is investigated from three perspectives: total connectedness, total directional connectedness, and pairwise directional connectedness. We find that the total connectedness of crude oil prices is 67.3%. We also find that the crude oil prices of Tapes, Daqing, Dubai and Minas are highly affected by Brent and WTI (West Texas Intermediate) crude oil prices. Furthermore, WTI and Brent are the price makers of international crude oil prices, while Tapes, Daqing, Dubai and Minas are price takers. From the perspective of pairwise directional connectedness, we find that the degree of pairwise directional connectedness between Brent and WTI are high. Finally, the structure of international crude oil markets stays the same even after market shocks. The main contributions of this study are identification of dynamic connectedness and presentation of the network connectedness of international crude oil prices.

An Empirical Investigation of Factors Affecting Stock Prices in Vietnam

2014 ◽  
pp. 74-89 ◽  
Author(s):  
Vinh Vo Xuan
Keyword(s):  
Exchange Rates ◽  
Crude Oil ◽  
Foreign Exchange ◽  
Stock Prices ◽  
Global Financial Crisis ◽  
Oil Prices ◽  
Foreign Exchange Rates ◽  
Factors Affecting ◽  
Crude Oil Prices ◽  
Before And After

This paper investigates factors affecting Vietnam’s stock prices including US stock prices, foreign exchange rates, gold prices and crude oil prices. Using the daily data from 2005 to 2012, the results indicate that Vietnam’s stock prices are influenced by crude oil prices. In addition, Vietnam’s stock prices are also affected significantly by US stock prices, and foreign exchange rates over the period before the 2008 Global Financial Crisis. There is evidence that Vietnam’s stock prices are highly correlated with US stock prices, foreign exchange rates and gold prices for the same period. Furthermore, Vietnam’s stock prices were cointegrated with US stock prices both before and after the crisis, and with foreign exchange rates, gold prices and crude oil prices only during and after the crisis.

Determinants of Inflation in Vietnam: A VECM Approach

2015 ◽  
Vol 22 (04) ◽  
pp. 26-50
Author(s):  
Ngoc Tran Thi Bich ◽  
Huong Pham Hoang Cam
Keyword(s):  
Interest Rate ◽  
Crude Oil ◽  
Error Correction ◽  
Budget Deficit ◽  
Oil Prices ◽  
Crude Oil Prices ◽  
Domestic Credit ◽  
Short Run ◽  
The Impact

This paper aims to examine the main determinants of inflation in Vietnam during the period from 2002Q1 to 2013Q2. The cointegration theory and the Vector Error Correction Model (VECM) approach are used to examine the impact of domestic credit, interest rate, budget deficit, and crude oil prices on inflation in both long and short terms. The results show that while there are long-term relations among inflation and the others, such factors as oil prices, domestic credit, and interest rate, in the short run, have no impact on fluctuations of inflation. Particularly, the budget deficit itself actually has a short-run impact, but its level is fundamentally weak. The cause of the current inflation is mainly due to public's expectations of the inflation in the last period. Although the error correction, from the long-run relationship, has affected inflation in the short run, the coefficient is small and insignificant. In other words, it means that the speed of the adjustment is very low or near zero. This also implies that once the relationship among inflation, domestic credit, interest rate, budget deficit, and crude oil prices deviate from the long-term trend, it will take the economy a lot of time to return to the equilibrium state.

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