International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks

Energy ◽  
2016 ◽  
Vol 101 ◽  
pp. 558-565 ◽  
Author(s):  
Ripsy Bondia ◽  
Sajal Ghosh ◽  
Kakali Kanjilal
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Structural Breaks ◽  
Oil Prices ◽  
Clean Energy ◽  
Crude Oil Prices ◽  
Cointegration Tests ◽  
Non Linear

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.

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.

tCO2e—a new pricing model for LNG?

2020 ◽  
Vol 13 (1) ◽  
pp. 83-87
Author(s):  
Peter Roberts
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Oil Prices ◽  
Clean Energy ◽  
Liquefied Natural Gas ◽  
Pricing Model ◽  
Crude Oil Prices ◽  
Value Measure ◽  
The Way

Abstract The concept of commercializing natural gas through liquefaction to give liquefied natural gas (LNG), with the capacity for that LNG to be shipped worldwide to meet the demand for clean energy, is well known. The options for, and the opportunities for evolution in, how LNG is priced (whether locally, regionally or even globally, with indexation to crude oil prices or to reported gas hub prices) have also been widely discussed in industry literature. But into the LNG pricing mix, we could soon be adding a new value measure which could have the capacity to shape the way in which LNG production projects are configured—tCO2e (or, to give it its full name, tCO2e/tLNG).

scholarly journals Linear and Non-Linear Modelling of Nigerian Crude Oil Prices

2021 ◽  
pp. 52-63
Author(s):  
Wiri Leneenadogo ◽  
Sibeate Pius U
Keyword(s):  
Crude Oil ◽  
Linear Model ◽  
Regime Switching ◽  
Linear Models ◽  
Nonlinear Models ◽  
Oil Prices ◽  
Information Criterion ◽  
Ar Model ◽  
Crude Oil Prices ◽  
Non Linear

To model Nigeria crude oil prices, this analysis compared univariate linear models to univariate nonlinear models. The data for this analysis was gathered from the Central Bank of Nigeria (CBN) Monthly Statistical Bulletin. The upward and downward movement in the series revealed by the time plot suggests that the series exhibit a regime-switching pattern: the cycle of expansion and contraction. At lag one, the Augmented Dickey-Fuller test was used to test for stationarity. For univariate linear ARIMA (p, d, q)) and univariate non-linear MS-AR, seven models were estimated for the linear model and two for the non-linear model. The best model was chosen based on the criterion of least information criterion,  AIC (2.006612), SC (2.156581), and the maximum log-likelihood of   (-150.5480) for the crude oil prices were used to pick MS-AR (1) for the series. In analysing crude oil prices data, the MS-AR model proposed by Hamilton outperforms the linear autoregressive models proposed by Box- Jenkins. The model was used to predict the series' values over a one-year cycle (12 months).

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