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A New Grey Relational Analysis Model Based on the Characteristic of Inscribed Core (IC-GRA) and Its Application on Seven-Pilot Carbon Trading Markets of China

机译:基于内接核特征的灰色关联分析新模型及其在中国七个试点碳交易市场中的应用

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摘要

In recent years, the study of the factors affecting the carbon trading price plays an important role in promoting the carbon trading markets and the sustainable development of green economy. However, due to the short establishment time of China’s carbon trading market, the carbon trading price data of the pilot markets were not complete and have the typical characteristics of poor information. The traditional grey correlation model cannot effectively identify the volatility and the grey correlation coefficient of trading data. In this paper, an inscribed cored grey relational analysis model (IC-GRA) is constructed by extracting the values of the triangle inscribed center of the time series sample. Through numerical examples and empirical analysis, it is verified that IC-GRA not only satisfies the four axioms of traditional grey correlation but also avoids the influence of outliers of time series fluctuation and improves the discriminability of the grey correlation coefficient. The empirical results of the IC-GRA model in China’s seven pilot carbon trading markets show that: 1. among international carbon trade factor, the biggest influence factor carbon trade price is different in pilot markets. The price of natural gas has a greater correlation with the carbon price of carbon trading markets in Shenzhen, Guangzhou, and Chongqing. The futures price of Certified Emission Reduction (CER) has a strong correlation with the carbon price of Shanghai and Beijing carbon trading markets; the price of Hubei carbon trading market is the largest related to crude oil future price in the New York Mercantile Exchange ( NYMEX). 2. Air Quality Index (AQI) is most relevant to the market carbon price of carbon trading, followed by the trading turnover and trading volume of the carbon trading market. Therefore, studying the carbon trading price of the carbon trading market plays a positive role in improving the sustainable development in those areas.
机译:近年来,对影响碳交易价格的因素的研究对促进碳交易市场和绿色经济的可持续发展具有重要作用。但是,由于中国碳交易市场的建立时间短,试点市场的碳交易价格数据不完整,具有信息匮乏的典型特征。传统的灰色关联模型无法有效识别交易数据的波动性和灰色关联系数。本文通过提取时间序列样本的三角形内接中心值,构建了内接核灰色关联分析模型(IC-GRA)。通过数值算例和实证分析,证明了IC-GRA不仅满足传统灰度相关性的四个公理,而且避免了时间序列波动离群值的影响,提高了灰度相关性的判别力。 IC-GRA模型在中国七个试点碳交易市场中的经验结果表明:1.在国际碳交易因素中,最大的影响因素碳交易价格在试点市场中有所不同。天然气价格与深圳,广州和重庆的碳交易市场的碳价格具有更大的相关性。核证减排量(CER)的期货价格与上海和北京碳交易市场的碳价格密切相关;湖北碳交易市场的价格是纽约商品交易所(NYMEX)与原油期货价格相关的最大价格。 2.空气质量指数(AQI)与碳交易的市场碳价最相关,其次是碳交易市场的交易量和交易量。因此,研究碳交易市场的碳交易价格对促进这些地区的可持续发展具有积极的作用。

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