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

Bondia, Ripsy; Ghosh, Sajal; Kanjilal, Kakali

doi:10.1016/j.energy.2016.02.031

Cited by 247 publications

(133 citation statements)

References 28 publications

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“…If the linear combination of these non-stationary variables can form a stationary time series, the resulting linear combination is called a co-integration equation, which means these variables exhibit a co-integration relationship. In this paper, the Johansen multivariate co-integration test method (Engle and Granger 1987;Bondia et al 2016;Ouyang and Lin 2015;Johansen 1988;Johansen and Juselius 1990;Moore and Copeland 1995) is used to carry out the co-integration test. The Johansen co-integration test is based on VAR.…”

Section: Co-integration Theorymentioning

confidence: 99%

“…The Johansen co-integration test method previously introduced in Sect. 3.2.1 is used to carry out the co-integration test to examine whether there is a long-term stable relationship between variables (Engle and Granger 1987;Bondia et al 2016;Ouyang and Lin 2015;Johansen 1988;Johansen and Juselius 1990;Moore and Copeland 1995). According to the co-integration theory Eqs.…”

Section: Johansen Co-integration Testmentioning

confidence: 99%

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Economics, fundamentals, technology, finance, speculation and geopolitics of crude oil prices: an econometric analysis and forecast based on data from 1990 to 2017

et al. 2018

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It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencing international crude oil prices and to establish crude oil price models to forecast long-term international crude oil prices. Six explanatory influential variables, namely Dow Jones Indexes, the Organization for Economic Cooperation and Development oil stocks, US rotary rig count, US dollar index, total open interest, which is the total number of outstanding contracts that are held by market participants at the end of each day, and geopolitical instability are specified, and the samples, from January 1990 to August 2017, are divided into six sub-periods. Moreover, the co-integration relationship among variables shows that the contribution ratios of all the variables influencing Brent crude oil prices are in accordance with the corresponding qualitative analysis.

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Section: Co-integration Theorymentioning

confidence: 99%

Section: Johansen Co-integration Testmentioning

confidence: 99%

Economics, fundamentals, technology, finance, speculation and geopolitics of crude oil prices: an econometric analysis and forecast based on data from 1990 to 2017

et al. 2018

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“…The basic matching mostly considers the propulsive efficiency, open water propeller efficiency mainly, as the single design objective in the conventional or complex propulsion system. Recently some other objectives and constraints have been considered in the system matching, taking not only the energy conversion efficiency, but also the ship operating cost and environmental impact into account [20]. Esmailian et al developed the approach to optimize the propeller-hull system simultaneously with two objective functions considered, i.e., lifetime fuel consumption (LFC) and the cost function including thrust, torque and open water propeller efficiency, to design a hull-propeller system with minimum LFC and cost [21].…”

Section: Introductionmentioning

confidence: 99%

Influence of EEDI (Energy Efficiency Design Index) on Ship–Engine–Propeller Matching

Ren

Ding

Sui

2019

JMSE

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With the increasingly strict international GHG (greenhouse gas) emission regulations, higher requirements are placed on the propulsion system design of conventional ships. Playing an important role in ship design, construction and operation, ship–engine–propeller matching dominantly covers the CO2 emission of the entire ship. In this paper, firstly, a ship propulsion system matching platform based on the ship–engine–propeller matching principle and its application on WinGD 5 × 52 marine diesel engine have been investigated. Meeting the energy efficiency design index (EEDI) regulation used to calculate the ship CO2 emission is essential and ship–engine–propeller matching has to be carried out with EEDI into consideration. Consequently, a procedure is developed combining the system matching theory and EEDI calculation, which can provide the matching results as well as the corresponding EEDI value to study the relationship between EEDI and ship–engine–propeller matching. Furthermore, a comprehensive analysis is performed to obtain the relationship of EEDI and system matching parameters, such as ship speed, effective power and propeller diameter, reflecting the trend and extent of EEDI when changing these three parameters. The results of system matching parameters satisfying different EEDI phases indicate the initial value selection in matching process to provide reference for the design of ship, engine and propeller under the EEDI regulations.

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“…Some studies have explored causality between oil prices and renewables, finding evidence of Granger causality that differs across sample periods and time horizons ( [2][3][4][5][6]). Other studies have examined oil price spillovers to renewable stocks, documenting significant impacts from oil price oscillations to renewable stock prices ( [7][8][9]), volatility spillovers between oil and clean-energy stocks ( [10][11][12]) and connectedness between clean energy stocks, oil prices and financial variables ( [13]). Likewise, a different set of articles have explored dynamic correlations between renewable energy and stock prices ( [14]) and the contribution of energy prices to renewable asset prices and volatility ( [15][16][17]).…”

Section: Introductionmentioning

confidence: 99%

Interdependence Between Renewable-Energy and Low-Carbon Stock Prices

2019

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In the transition to a low-carbon economy, climate-resilient investors may be inclined to buy renewable-energy or other low-carbon assets. As the diversification benefits of investment positions in those assets depend on interdependence between their market prices, we explore that interdependence in the European and USA stock markets. We model the dependence structure using bivariate copula functions and evaluate price spillovers between those markets using a conditional quantile dependence approach that accounts for the reciprocal effects of price movements in those markets under normal and extreme market scenarios. Our empirical evidence for the period 2010–2019 indicates that European renewable-energy and low-carbon stocks co-move; upward and downward movements in low-carbon asset prices have sizeable effects on renewable-energy asset prices, and vice versa, although effects are smaller. In contrast, for the USA we find evidence of non-interdependence, with no significant upward or downward price spillover effects between renewable-energy and low-carbon stocks. Our empirical findings provide useful insights for the design of carbon-resilient portfolios and risk management strategies, and also for implementation of public funding policies to support the transition to a low-carbon economy.

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

Cited by 247 publications

References 28 publications

Economics, fundamentals, technology, finance, speculation and geopolitics of crude oil prices: an econometric analysis and forecast based on data from 1990 to 2017

Economics, fundamentals, technology, finance, speculation and geopolitics of crude oil prices: an econometric analysis and forecast based on data from 1990 to 2017

Influence of EEDI (Energy Efficiency Design Index) on Ship–Engine–Propeller Matching

Interdependence Between Renewable-Energy and Low-Carbon Stock Prices

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