How do fossil energy prices affect the stock prices of new energy companies? Evidence from Divisia energy price index in China's market

Sun, Chuanwang; Ding, Dan; Fang, Xingming; Zhang, Huiming; Li, Jianglong

doi:10.1016/j.energy.2018.12.032

Cited by 151 publications

(46 citation statements)

References 25 publications

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“…Further, we will employ the cointegration test developed by Johansen [70]. We will consider a VAR of the order, p [13][14][15]22,25,35,40,44,45,65]:…”

Section: Econometric Methodsmentioning

confidence: 99%

“…For China, Luo and Qin [14] found that oil price shocks positively influence Chinese stock returns, whereas oil price volatility shocks have a negative effect. Also, Sun et al [15] documented that fossil energy prices had a positive influence on new energy stock prices. Similarly, Salisu et al [16] established that economic agents functioning in the US stock market are inclined to respond more to positive oil price shocks than the negative ones.…”

Section: Introductionmentioning

confidence: 99%

“…The energy market can undoubtedly be a driver of economic growth and job creation in a developing country, such as Romania. Previous examinations were undertaken for African stock markets [20,23], Asian countries [6,14,15,[24][25][26][27][28], European nations [18,29], the US stock market [1,16,[30][31][32], Egypt [33], Gulf states [7,34,35], India [36], Islamic stocks [19], Lebanon [37], Mexico [38,39], and Turkey [40,41]. To the best of our knowledge, this is the first investigation to examine the linkage between the energy market and the Romanian stock market.…”

Section: Introductionmentioning

confidence: 99%

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On the Linkage between the Energy Market and Stock Returns: Evidence from Romania

2019

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his paper aims to establish whether the Romanian energy market has an influence on the good running of the associated capital market. In order to achieve this objective, we approached a series of econometric techniques that allowed us to study the cointegration between variables, the presence of short-term or long-term causality relationships, and the application of impulse-response functions to analyze how the BET index responds to the shocks applied. The empirical findings from the Johansen cointegration test, ARDL model, and VAR/VECM models confirmed both the presence of a long-term and short-term relationship between the energy market and capital market. From all energy market indicators, only hard coal presented a causal relationship with the BET index. We also noticed a unidirectional relationship from the WTI crude oil to the Romanian capital market. Our findings should be of interest to researchers, regulators, and market participants.

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“…Further, we will employ the cointegration test developed by Johansen [70]. We will consider a VAR of the order, p [13][14][15]22,25,35,40,44,45,65]:…”

Section: Econometric Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the Linkage between the Energy Market and Stock Returns: Evidence from Romania

2019

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“…Besides, considering the fact that China's energy consumption structure dominated by coal and steam coal is the main power consumption for many industries, we select the steam coal price to represent China's coal market price [38]. Meanwhile, in light of Sun et al [39], we choose future price not spot price as a proxy for two reasons. First, the spot price of the steam coal may fluctuate frequently due to it only pays attention to the short-run demand and supply and the price.…”

Section: Datamentioning

confidence: 99%

Time-frequency Connectedness between Coal Market Prices, New Energy Stock Prices and CO2 Emissions Trading Prices in China

Jiang

et al. 2020

Sustainability

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This paper aims to examine whether there is inherent dynamic connectedness among coal market prices, new energy stock prices and carbon emission trading (CET) prices in China under time- and frequency-varying perspectives. For this purpose, we apply a novel wavelet method proposed by Aguiar-Conraria et al. (2018). Specifically, utilizing the single wavelet power spectrum, the multiple wavelet coherency, the partial wavelet coherency, also combined with the partial phase difference and the partial wavelet gains, this paper discovers the time-frequency interaction between three markets. The empirical results show that the connectedness between the CET market price and the coal price is frequency-varying and mainly occur in the lower and higher frequency bands, while the connectedness between the CET market price and the new energy stock price mainly happen in the middle and lower frequency bands. In the high-frequency domain, the CET market price is mainly affected by the coal price, while the CET market price is dominated by the new energy stock price in the middle frequency. These uncovered frequency-varying characteristics among these markets in this study could provide several implications. Main participants in these markets, such as polluting industries, governments and financial actors, should pay close attention to the connectedness under different frequencies, in order to realize their goal of the production, the policymaking, and the investment.

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“…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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How do fossil energy prices affect the stock prices of new energy companies? Evidence from Divisia energy price index in China's market

Cited by 151 publications

References 25 publications

On the Linkage between the Energy Market and Stock Returns: Evidence from Romania

On the Linkage between the Energy Market and Stock Returns: Evidence from Romania

Time-frequency Connectedness between Coal Market Prices, New Energy Stock Prices and CO2 Emissions Trading Prices in China

Interdependence Between Renewable-Energy and Low-Carbon Stock Prices

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