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Zhu Dandan; Zhang Chen; Pan Di; Hu Shu. Multifractal cross-correlation analysis between carbon spot and futures markets considering asymmetric conduction effect. Fractals 2021, 1 .
AMA StyleZhu Dandan, Zhang Chen, Pan Di, Hu Shu. Multifractal cross-correlation analysis between carbon spot and futures markets considering asymmetric conduction effect. Fractals. 2021; ():1.
Chicago/Turabian StyleZhu Dandan; Zhang Chen; Pan Di; Hu Shu. 2021. "Multifractal cross-correlation analysis between carbon spot and futures markets considering asymmetric conduction effect." Fractals , no. : 1.
Carbon markets were set up with the aim to achieve carbon reduction target and sustainable development. However, market risk has become one of the key factors influencing continuous development of carbon markets. Different from traditional financial asset price, carbon price has a heterogeneous characteristic in its tail distribution. The current value at risk (VaR) model with student t or generalized error distribution (GED) cannot describe the asymmetric tail distribution of carbon price. Therefore, this article propose to develop a combined model for China's carbon market risk measurement. First, extend generalized autoregressive conditional heteroscedasticity (GARCH) with standardized standard asymmetric exponential power distribution (SSAEPD) to reflect volatility clustering phenomenon and heterogeneous distribution character of China's carbon price. Then, genetic algorithm (GA) was innovatively used to solve GARCH‐SSAEPD linear programming instead of interior‐point algorithm. Finally, use VaR to measure the carbon market risk. The new model (GARCH‐SSAEPD‐GA‐VaR) is implied to China's carbon market and compared with the traditional GARCH‐VaR model, the empirical results show: (a) Compared with current VaR framework, the GARCH‐SSAEPD‐GA‐VaR model we constructed can help describe the heterogeneous tail distribution of carbon price and help increase the precision of carbon market risk measurement. (b) SSAEPD can capture fat‐tail, asymmetric effects of China's carbon price more entirely, which puts forward a new method to study the evolvement laws of carbon market risk. (c) GA is effective to achieve global optimum to some extent in parameter estimation. This study contribute to developing theory and methodology of describing particularity features of carbon price, increasing the accuracy of carbon market risk measurement and provide a new perspective for investigating the evolvement regularity of China's carbon market risks.
Xianzi Yang; Chen Zhang; Yu Yang; Wenjun Wang; Zulfiqar Ali Wagan. A new risk measurement method for China's carbon market. International Journal of Finance & Economics 2020, 1 .
AMA StyleXianzi Yang, Chen Zhang, Yu Yang, Wenjun Wang, Zulfiqar Ali Wagan. A new risk measurement method for China's carbon market. International Journal of Finance & Economics. 2020; ():1.
Chicago/Turabian StyleXianzi Yang; Chen Zhang; Yu Yang; Wenjun Wang; Zulfiqar Ali Wagan. 2020. "A new risk measurement method for China's carbon market." International Journal of Finance & Economics , no. : 1.
To address climate change, the carbon emission trading scheme has become one of the main measures to achieve emission reduction goals. One of the core problems in constructing the carbon emissions trading market is determining carbon emissions trading prices. The scientific nature of carbon emissions pricing determines the effectiveness of market regulation. Research on the influencing factors and heterogeneous tail distribution of carbon prices can increase the accuracy of carbon pricing, which is particularly important for the development of the carbon emissions trading market. The current studies have some limitations and lack heterogeneous tail description. We employ the arbitrage pricing theory-standardized standard asymmetric exponential power distribution model to analyze China’s regional carbon emissions trading price and use a genetic algorithm to solve linear programming. The results confirm the theoretical results and efficiency of the proposed algorithm. First, the new model can capture the skewness, fat-tailed distribution, and asymmetric effects of China’s regional carbon emissions trading price. Second, the macroeconomy, similar products, energy price, and exchange rate influence the carbon price fluctuation; investors’ behavior plays an important role in the heterogeneous tail distribution of carbon price. The findings provide references for the government to take appropriate measures to promote carbon emission reduction and improve the effectiveness of China’s carbon market. Therefore, our findings can help enhance emission reduction and achieve sustainable development of a low-carbon environment.
Xianzi Yang; Chen Zhang; Yu Yang; Yaqi Wu; Po Yun; Zulfiqar Ali Wagan. China’s Carbon Pricing Based on Heterogeneous Tail Distribution. Sustainability 2020, 12, 2754 .
AMA StyleXianzi Yang, Chen Zhang, Yu Yang, Yaqi Wu, Po Yun, Zulfiqar Ali Wagan. China’s Carbon Pricing Based on Heterogeneous Tail Distribution. Sustainability. 2020; 12 (7):2754.
Chicago/Turabian StyleXianzi Yang; Chen Zhang; Yu Yang; Yaqi Wu; Po Yun; Zulfiqar Ali Wagan. 2020. "China’s Carbon Pricing Based on Heterogeneous Tail Distribution." Sustainability 12, no. 7: 2754.
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.
Po Yun; Chen Zhang; Yaqi Wu; Xianzi Yang; Zulfiqar Ali Wagan. A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network. Sustainability 2020, 12, 1869 .
AMA StylePo Yun, Chen Zhang, Yaqi Wu, Xianzi Yang, Zulfiqar Ali Wagan. A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network. Sustainability. 2020; 12 (5):1869.
Chicago/Turabian StylePo Yun; Chen Zhang; Yaqi Wu; Xianzi Yang; Zulfiqar Ali Wagan. 2020. "A Novel Extended Higher-Order Moment Multi-Factor Framework for Forecasting the Carbon Price: Testing on the Multilayer Long Short-Term Memory Network." Sustainability 12, no. 5: 1869.
The wandering weekday effect of the international carbon market is a neglected topic. This paper investigates the wandering weekday effect of the international carbon market under the moderation effect of market trend. Our results show that there is a positive wandering Monday and negative wandering Tuesday effect when the market is rising, and a negative wandering Monday and positive wandering Tuesday effect when the market is falling. Further studies find that the settlement procedures, information disclosure and the determinants of carbon prices are stronger reasons of the wandering weekday effect. The conclusion provides new evidence for the study of market-efficiency in international carbon market.
Chen Zhang; Po Yun; Zulfiqar Ali Wagan. Study on the wandering weekday effect of the international carbon market based on trend moderation effect. Finance Research Letters 2019, 28, 319 -327.
AMA StyleChen Zhang, Po Yun, Zulfiqar Ali Wagan. Study on the wandering weekday effect of the international carbon market based on trend moderation effect. Finance Research Letters. 2019; 28 ():319-327.
Chicago/Turabian StyleChen Zhang; Po Yun; Zulfiqar Ali Wagan. 2019. "Study on the wandering weekday effect of the international carbon market based on trend moderation effect." Finance Research Letters 28, no. : 319-327.
In order to explore the factors and their complex mechanism affecting the price dynamics under the clean development mechanism (CDM), this article employs the secondary Certified Emission Reduction (sCER) carbon price as the study object, and analyzes its influencing factors from aspects of the international carbon-reduction policies, macroeconomic fluctuations, energy and similar carbon products prices. The innovation of this paper lies in: Introducing necessary factor (the developing countries pricing power) and the application of several international representative indicators to underline the “world” nature of CDM; utilizing different econometric models to obtain noteworthy and more robust results. The authors test the theoretical findings with multiple stationary time series from the launch of CDM to present (2008–2016). The results reveal that sCER price fluctuation shows the characteristic of asymmetry and substantial persistence. There is a strong statistically significant relationship between macroeconomic conditions, coal and oil prices, with the price of sCER. The authors discover that the pricing power of developing countries indeed has a clear but small impact on the sCER price changes, whereas the price elasticity of supply under CDM is so weak. The interaction between EU emission allowances (EUAs) and sCER presents a shift from dependency to substitution.
Chen Zhang; Yaqi Wu; Yu Yang. The Influencing Factors of sCER Price Dynamics Under the Clean Development Mechanism: Theory and Econometric Analysis. Journal of Systems Science and Complexity 2018, 31, 1244 -1272.
AMA StyleChen Zhang, Yaqi Wu, Yu Yang. The Influencing Factors of sCER Price Dynamics Under the Clean Development Mechanism: Theory and Econometric Analysis. Journal of Systems Science and Complexity. 2018; 31 (5):1244-1272.
Chicago/Turabian StyleChen Zhang; Yaqi Wu; Yu Yang. 2018. "The Influencing Factors of sCER Price Dynamics Under the Clean Development Mechanism: Theory and Econometric Analysis." Journal of Systems Science and Complexity 31, no. 5: 1244-1272.