PRICING CARBON CREDITS BASED ON MODIFIED BLACK-SCHOLES

Pub Date : 2023-01-01 DOI:10.30638/eemj.2023.037
Yi Song, D. Chang
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Abstract

In order to develop the carbon emission market in a positive and healthy direction, how to price carbon emission rights effectively is an issue worth studying. This paper compares the advantages, disadvantages and applicability of several commonly used pricing methods, and finally chooses the Black-Scholes model (hereinafter referred to as ‘B-S’ model) as the base model to carry out the study. Since the volatility of carbon emission rights is subject to fluctuations, the historical volatility in the BS model cannot fully reflect the real market situation. In order to solve this problem, the GARCH model is introduced to fit the volatility of returns to improve the accuracy of the BS model. However, as the amount of data increases, the modeling ability of the GARCH model cannot fully simulate volatility. The GARCH model is the most commonly used model for modeling the volatility of financial time series data, while the LSTM model requires high initial values. The combination of the two models improves the accuracy of the model and is tested by empirical evidence. The results of this paper enrich the theoretical system of carbon emission rights assessment.
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基于修改后的黑分数为碳信用定价
为了使碳排放市场朝着积极健康的方向发展,如何对碳排放权进行有效定价是一个值得研究的问题。本文比较了几种常用的定价方法的优缺点和适用性,最终选择Black-Scholes模型(以下简称“B-S”模型)作为基础模型进行研究。由于碳排放权的波动率会受到波动的影响,因此BS模型中的历史波动率并不能完全反映真实的市场情况。为了解决这一问题,引入GARCH模型来拟合收益的波动性,以提高BS模型的准确性。然而,随着数据量的增加,GARCH模型的建模能力并不能完全模拟波动率。GARCH模型是金融时间序列数据波动率建模最常用的模型,而LSTM模型对初始值要求较高。两种模型的结合提高了模型的准确性,并得到了经验证据的检验。本文的研究成果丰富了碳排放权评估的理论体系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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