Carbon option pricing based on uncertain fractional differential equation: A binomial tree approach

China's carbon emission trading market has gradually attracted worldwide attention. In this paper, a structural VAR model and Shenzhen, a typical city in China, are selected to study the dynamic relationships between China's carbon emission rights price, energy prices, macroeconomic level, and weather conditions. Shanghai crude oil futures, the first crude oil futures contract in China, is used to describe changes in oil market as a substitute for Daqing crude oil price. The results show that the price of carbon emission rights is mainly affected by its own historical price; and the price of carbon emission rights is positively correlated with crude oil price and natural gas price, but negatively correlated with coal price; the change of macroeconomic level will still have a relatively large impact on carbon emission rights price in the current stage of economic development in China, but this impact is not significant; The impact of weather conditions on the price of carbon emission rights is not obvious. It is found that the launch of the national unified carbon market has indeed achieved certain results, but the situation that China's carbon market is still in its infancy has not been changed; further efforts are needed.

Coking coal is a vital energy resource for economic development, with fluctuations in coking coal futures prices significantly guiding spot prices. Additionally, variations in carbon emission rights prices directly affect China's energy conservation and emission reduction efforts. This paper examines the daily trading prices of carbon emission rights and coking coal futures. It utilizes various tests, including the ADF test and cointegration test, and constructs a two-dimensional vector autoregression (VAR) model with a two-period lag. The paper also performs an impulse response function analysis and variance decomposition. Empirical results reveal: First, the daily trading prices of coking coal futures have exhibited a fluctuating upward trend over the past six years; Second, there is a long-term cointegration relationship between coking coal futures prices and carbon emission rights prices; Third, there is no Granger causality between the two; Fourth, fluctuations in carbon emission rights prices have a stronger guiding effect on coking coal futures prices than vice versa. Recommendations include: (1) Strengthening oversight of the coking coal futures market and leveraging policy guidance to prevent extreme prices; (2) Systematically including more participants in the carbon market, optimizing the trading structure, and promoting healthy market development; (3) When developing policies for carbon emission rights, the government should mitigate the impact of price fluctuations on other sectors.

Bidding strategy optimization for power generation company in carbon emission rights and electricity market

The relentless exacerbation of the greenhouse effect poses a significant challenge to the progress and sustainability of human civilization. Carbon emission rights serve as a pivotal gauge of the carbon trading market's dynamics. Examining the impact of carbon emission rights prices can shed light on how governments indirectly influence these prices through mechanisms such as carbon emission quotas and permits. This study focuses on analyzing the transaction prices of carbon emission rights quotas within the Guangzhou carbon trading market spanning from January 2015 to March 2023. Leveraging a selection of 17 variables across the realms of energy prices, macroeconomics, financial markets, and ecological environment, and drawing insights from the predictive outcomes of three distinct sub-models—namely Ridge Regression, Random Forest Regression, and Long Short-Term Memory neural network (LSTM)—a novel IOWHA operator vector angle cosine combination model is devised. The findings underscore that this combined model harnesses the predictive strengths of each sub-model, effectively curbing prediction discrepancies, and enhancing overall accuracy. The integration of these methodologies represents an optimal fusion for predictive modeling.

The carbon emission rights do not fit well into the framework of existing multi‐item auction mechanisms because of their own unique features. This paper proposes a new auction mechanism which converges to a unique Pareto optimal equilibrium in a finite number of periods. In the proposed auction mechanism, the assignment outcome is Pareto efficient and the carbon emission rights’ resources are efficiently used. For commercial application and theoretical completeness, both discrete and continuous markets—represented by discrete and continuous bid prices, respectively—are examined, and the results show the existence of a Pareto optimal equilibrium under the constraint of individual rationality. With no ties, the Pareto optimal equilibrium can be further proven to be unique.

The impact of Renewable Portfolio Standards on carbon emission trading under the background of China’s electricity marketization reform

In the spring of 2022, a new round of epidemic broke out in Shanghai, causing a shock to the Shanghai carbon trading market. Against this background, this paper studied the impact of the new epidemic on the price of Shanghai carbon emission rights and tried to explore the prediction model under the unexpected event. First, because a model based on point value data cannot capture the information hidden in inter-day price fluctuation, based on the interval price of Shanghai carbon emission rights (SHEA) and its influencing factors, an autoregressive conditional interval model with jumping and exogenous variables (ACIXJ) was established to explore the influence of the Russian–Ukrainian conflict and COVID-19 on the interval price of SHEA, respectively. The empirical results show that the conflict between Russia and Ukraine has no obvious influence on the price of SHEA, but COVID-19 led to a decline in the price trend of SHEA over four days before the city was closed, and the volatility changed significantly on the day before the city was closed. The price fluctuation was the strongest within 3 days after the city was closed; In addition, in order to accurately predict the interval data of SHEA against the background of COVID-19, based on the interval data decomposition algorithm (BEMD), a hybrid forecasting model of NDGM-ACIXJ/CNN-LSTM was constructed, in which the discrete gray model of approximate nonhomogeneous exponential series (NDGM) combined with the ACIXJ model is used to predict the high-frequency sub-interval, and the convolution neural network long-term and short-term memory model (CNN-LSTM) is used to predict the low-frequency sub-interval. The empirical results show that the prediction model proposed in this article has higher prediction precision than the reference models (ACIX, ACIXJ, NDGM-ACIXJ, BEMD-ACIX/CNN-LSTM, BEMD-ACIXJ/CNN-LSTM).

Low-carbon power dispatch with wind power based on carbon trading mechanism

Carbon credits should reduce the environmental pollution and carbon emission of the Earth in the future. The market for carbon credits will become a critical issue from 2021, and carbon credits will be applied to systems where individuals can trade. In order for these carbon credits to be traded between individuals, however, a corresponding exchange of carbon credits is needed. Policies, strategies, and technologies are also necessary to measure the trading of carbon credits. This paper aims at making transactions more reliable by applying blockchain technology to measure carbon emission rights. It uses blockchain to verify carbon emissions rights among the UN-SDGs’ (United Nations Sustainable Development Goals’) 17 tasks. In addition, it introduces the necessary dApp. In fact, we can protect against carbon emissions anomalies by using big data and artificial intelligence in mobile cloud environments. Thus, this paper proposes a blockchain-based carbon emission rights verification system to learn proven data further by using the governance system analysis and blockchain mainnet engine to solve these problems.

In light of the growing demand for sustainable behavior and the special interest that has emerged regarding the social and environmental impact of firms, the purpose of this research is to analyze the determinants of the accounting treatment of emission rights. To achieve that purpose, we use a sample composed of 119 firms worldwide from different countries and activity sectors for the period 2011. Our findings show different accounting treatments depending on a series of factors. Specifically, firms pertaining to countries that have adopted Environmental Trading Schemes (ETS) tend to account for emission rights through provisions, investments, or as inventory. For their part, firms that issue indicators that appear in the report drawn up by KPMG and GRI (2007) tend to account for these entries as expenses, especially as R + D expenses. Finally, firms located in countries that signed the Kyoto protocol have a tendency to not account for carbon emission rights. The findings of this work can be considered of great interest on the international level because our research contributes to the scant previous literature regarding the accounting treatment of emission rights.

In recent years, the rapid increase in CO2 concentration has accelerated global warming. As a result, sea levels rise, glaciers melt, extreme weather occurs, and species become extinct. As the world’s largest CO2 emission rights trading market, EU Emissions Trading System (EU-ETS) has reached 1.855 billion tons of quotas by 2019, influencing the development of the global carbon emission market. Crude oil, as one of the major fossil energy sources in the world, its price fluctuation is bound to affect the price of carbon emission rights. Therefore, this paper aims to reveal the correlation between crude oil futures prices and carbon emission rights futures prices by studying the price fluctuation. In this paper, the linkage between West Texas Intermediate (WTI) crude oil futures prices and European carbon futures prices was investigated. In addition, this paper selects continuous data of WTI crude oil futures prices and spot prices with European carbon futures prices from January 8, 2018 to November 27, 2020, and builds a smooth transformation regression (STR) model. The relationship between crude oil futures and carbon futures prices is studied in both forward and reversal linkage through empirical analysis. The results show that crude oil futures prices and carbon futures prices have a mutual effect on each other, and both linear and nonlinear correlations between the two prices exist. Based on the results of this research, some suggestions are provided.

The essence of carbon emission right is a legalized right, and carbon emission right trading is to commercialize this right based on the market. This paper uses panel data of 226 prefecture-level cities in China from 2007 to 2016 as samples to examine the effect and mechanism of carbon emission trading policies on urban carbon emission intensity. The study found that the carbon emission trading policy has a significant promotion of reducing carbon emission, with the adjustment of industrial structure and energy-saving emission reduction methods. It can effectively reduce the city’s carbon emission.

The carbon emission rights trading pilot (CERTP) policy is an important measure to promote low-carbon economic development. This pilot policy also affects the entry and survival of enterprises and is thus related to local government fiscal pressure. The objective of this paper is to examine whether the CERTP policy increases local government fiscal pressure. Based on the quasi-natural experiment of China's CERTP policy, using a dataset from 314 prefecture-level cities in China over the period 2005 to 2019, this paper applies the staggered difference-in-differences (DID) model to examine the impact of the CERTP policy on local government fiscal pressure, and further tests the spatial spillover effects and potential mediation mechanisms of this pilot policy. The results indicate that the implementation of the CERTP policy significantly increases local government fiscal pressure, especially in the eastern regions and regions with low economic development levels, which provides further evidence of a causal relationship between the CERTP policy and fiscal pressure. The results of the spatial spillover effects confirm that the implementation of the CERTP policy in neighboring prefecture-level cities would increase local government fiscal pressure in the local region. The results of the mediation mechanism effect reveal that the CERTP policy aggravates local government fiscal pressure by inhibiting the progress of green technology by enterprises, hindering the emergence of new enterprises, and increasing the number of closures of high-carbon emissions enterprises. This paper recommends that when implementing the CERTP policy, it is necessary to weigh the overall impact of the policy, not just its effect on carbon emissions reduction. The fiscal sustainability of local governments cannot be ignored.

Holistic coordination of transactive energy and carbon emission right trading for heterogenous networked multi-energy microgrids: A fully distributed adaptive consensus ADMM approach

Low-CO 2 energy pathways and regional air pollution in Europe