An empirical analysis of energy cost pass-through to CO 2 emission prices

Hammoudeh, Shawkat; Lahiani, Amine; Nguyen, Duc Khuong; Sousa, Ricardo M.

doi:10.1016/j.eneco.2015.02.013

Cited by 120 publications

(47 citation statements)

References 32 publications

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“…For instance, some papers found that the two markets are positively correlated, e.g., Alberola et al (2008) when considering breaks in the model, Chevallier (2009), Mansanet-Bataller et al (2011), Creti et al (2012, Reboredo and Ugando (2015), and Yu et al (2015), while some observed that they are otherwise negatively depended, e.g., Hammoudeh et al (2015).…”

Section: Accepted Manuscriptmentioning

confidence: 97%

“…Currently, some powerful techniques have also been introduced to capture the dynamic complex nonlinear relationship between carbon and oil markets, such as Copula function (Reboredo and Ugando, 2015), Nonlinear autoregressive model (e.g., Hammoudeh et al, 2015) and dynamic conditional correlation (DCC) model (e.g., Yu et al, 2015). Since most previous studies focused on linear or nonlinear relationship, this paper tends to integrate the linear and nonlinear Granger causality tests to capture both the linear and nonlinear relationship between the carbon and oil markets.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

See 1 more Smart Citation

Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach

Tang

et al. 2015

Energy Economics

149

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Section: Accepted Manuscriptmentioning

confidence: 97%

Section: Accepted Manuscriptmentioning

confidence: 99%

Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach

Tang

et al. 2015

Energy Economics

149

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“…Further evidence has verified that the shock of policy turbulence (like the implementation of carbon tax) and uncertainty in the energy and financial markets can easily affect the carbon price through financial channels [3]. In other words, the shock from the energy and financial markets will also have an impact on the carbon price forecast and price fluctuation.…”

Section: Introductionmentioning

confidence: 95%

A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network

Yun

Zhang

et al. 2020

Sustainability

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Predicting the carbon price accurately can not only promote the sustainability of the carbon market and the price driving mechanism of carbon emissions, but can also help investors avoid market risks and increase returns. However, previous research has only focused on the low-order moment perspective of the returns for predicting the carbon price, while ignoring the shock of extreme events and market asymmetry originating from its pricing factor markets. In this paper, a novel extended higher-order moment multi-factor framework (EHM-APT) was formed to improve the prediction and to capture the driving mechanism of the carbon price. Furthermore, a multi-layer and multi-variable Long Short-Term Memory Network (Multi-LSTM) model was constructed so that the parameters and structure could be determined experimentally for testing the performance of the proposed framework. The results show that the pricing framework considers the shock of extreme events and market asymmetry and can improve the prediction compared with a framework that does not consider the shock of higher-order moment terms. Additionally, the Multi-LSTM model is more competitive for prediction than other benchmark models. This conclusion proves the rationality and accuracy of the proposed framework. The application of the pricing framework encourages investors and financial institutions to pay more attention to the pricing factor of extreme events and market asymmetry for accurate price prediction and investment analysis.

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“…Marimoutou and Soury [21] show that the relationships between the energy market and the CO 2 emission market fluctuate over time. Hammoudeh et al [22] claim that the negative changes in coal prices can interpret the carbon market price better than the impact of positive changes in the short-term.…”

Section: Literature Reviewmentioning

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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An empirical analysis of energy cost pass-through to CO 2 emission prices

Cited by 120 publications

References 32 publications

Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach

Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach

A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network

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

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