Multifractality and market efficiency of carbon emission trading market: Analysis using the multifractal detrended fluctuation technique

Fan, Xinghua; Lv, Xiangxiang; Yin, Jiuli; Tian, Lixin; Liang, Jiaochen

doi:10.1016/j.apenergy.2019.113333

Cited by 54 publications

(15 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By looking carefully at the literature on the topic of market efficiency and studies that took placed in this area, it can be seen that several methods have been proposed to examine the market efficiency in carbon markets and we can classify them into several distinct categories. They include methods that rely on variance ratio (VR) tests (Daskalakis and Markellos 2008;Ibikunle et al 2012;Montagnoli and De Vries 2010;Niblock and Harrison 2013;Yang et al 2018;Zhang et al 2020;Zhou et al 2019), cost of carry models (Charles et al 2013;Joyeux and Milunovich 2010), and the profitability of trading strategies (Aatola et al 2014;Daskalakis and Markellos 2008;Daskalakis 2013;Niblock and Harrison 2013), and the methods based on multifractality tests and intermittency coefficient (Fan et al 2019;Sattarhoff and Gronwald 2018). In what follows, we tried to analyze the ideas presented in each of the mentioned studies.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In contrast, phase I and phase III fall short to carries attributes of an efficient market. Fan et al (2019) check the multifractality and efficiency of several pilots in the CO 2 market of China by applying the multifractal detrended fluctuation analysis (MFDFA) method. They evaluate the efficiencies in these markets by utilizing an indicator that they introduced based on the generalized Hurst exponents, and the findings imply prevalent inefficiencies among pilot markets.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The efficiency of CO2 market in the phase III EU ETS: analyzing in the context of a dynamic approach

Ghazani

Jafari

2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

This study has investigated the changing efficiency for the phase III EU ETS CO 2 market using the daily historical data of allowance future prices and coverage from August 2015 to December 2020. We have applied two alternative tests for checking dependency by linear and nonlinear methods to achieve this goal, including generalized spectral (GS) and automatic portmanteau (AQ). Also, we had a comprehensive look at the carbon market evolution and the EU ETS scheme development over time. The analysis of observed results validates the adaptive market hypothesis (AMH) in the market, which corresponds with the oscillatory behavior of the applied test statistics' p-values. The other aspect of the study was to analyze the existence of evolutionary behavior on the market. To reach this purpose, we checked the results by applying a rolling window technique with four different time windows (50, 100, 150, and 250 days) on the test statistics in harmony with the adaptive market hypothesis. The obtained results show that overall, market efficiency has been improved by implementing higher window lengths.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

The efficiency of CO2 market in the phase III EU ETS: analyzing in the context of a dynamic approach

Ghazani

Jafari

2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…Some scholars also studied the efficiency of China's ETS pilot provinces and cities with respect to the carbon price. Although inefficiency generally exists, the efficiency of most pilot provinces and cities increases over time [24][25][26][27][28][29]. Existing studies mainly focus on evaluating the mechanism of the effect of an ETS on the carbon intensity, carbon emissions, and GDP.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable Feasibility of Carbon Trading Policy on Heterogenetic Economic and Industrial Development

Zhang

et al. 2019

Sustainability

View full text Add to dashboard Cite

A carbon emission trading system (ETS) is an effective market mechanism for promoting the reduction of global greenhouse gas emissions and achieving sustainable development between the economy and the environment. To analyze the emissions reduction effect and economic effect of China’s ETS and further discuss the mechanisms of economic development differences and industrial development differences on the final effect of the policy, this study adopts the propensity score matching-difference in differences method and triple difference method. The empirical results show the following: (1) The ETS can simultaneously achieve both the emissions reduction effect and economic effect when key control variables are included. (2) The population, carbon emissions intensity and per capita GDP have significant positive impacts on carbon emissions; the environmental pollution control intensity, research structure, and research intensity have negative impacts on carbon emissions; and the capita stock, employment, and energy consumption have significant positive economic effects. (3) The ETS has a stronger inhibitory effect on the provinces with higher levels of economic and service development compared to the provinces with lower levels of economic and service development. In contrast, the policy has a weaker inhibitory effect on provinces with higher levels of industrial and construction development compared with the lower level provinces.

show abstract

“…Hence, it is necessary to forecast carbon prices accurately so as to enhance the enthusiasm of market participants. Evidence shows that carbon prices exhibit non-stationarity, nonlinearity, multi-scale and chaos (Fan et al, 2019 ; Huang et al, 2021 ; Manaf et al, 2016 ; Tian & Hao, 2020 ; Zhu et al, 2017 ; Zou & Zhang, 2020 ) and these make predictions difficult. Therefore, capturing features of carbon prices in order to maximise the forecasting precision is of great significance and it has become a challenging task for academic researchers.…”

Section: Introductionmentioning

confidence: 99%

Carbon price prediction for China's ETS pilots using variational mode decomposition and optimized extreme learning machine

Chai

Zhang

2021

Ann Oper Res

View full text Add to dashboard Cite

Multifractality and market efficiency of carbon emission trading market: Analysis using the multifractal detrended fluctuation technique

Cited by 54 publications

References 42 publications

The efficiency of CO2 market in the phase III EU ETS: analyzing in the context of a dynamic approach

The efficiency of CO2 market in the phase III EU ETS: analyzing in the context of a dynamic approach

Sustainable Feasibility of Carbon Trading Policy on Heterogenetic Economic and Industrial Development

Carbon price prediction for China's ETS pilots using variational mode decomposition and optimized extreme learning machine

Contact Info

Product

Resources

About