Dynamic interrelationships among crude oil, green bond, and carbon markets: Evidence from fuzzy logic autoencoders

IF 7.2 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Nini Johana Marín-Rodríguez , Elie Bouri , Juan David González-Ruiz , Sergio Botero , Alejandro Peña
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引用次数: 0

Abstract

This paper investigates the dynamic interrelationships among various markets covering crude oil, green bonds, and carbon emissions from January 2014 to October 2022, using a Fuzzy Logistic Autoencoder (FLAE) model, which elevates methodological sophistication and helps capturing intricate and complex relationships across the three markets. Different features of FLAE, such as identifying crossed lags and introducing a novel sigmoid-type activation function, enhance structural stability and establish the model as a reference for studying cross-temporal effects across markets. The key findings indicate that green bond returns negatively impact the returns of carbon emission allowances and Brent oil in the short and medium term. The impact of carbon emission allowance returns and oil returns on the forecast of green bond returns is comparatively trivial. Forecasting green bond returns is primarily driven by its short-term lags. These findings should be useful for portfolio managers in energy markets, environmentally conscious investors, and policy-makers concerned with financial sustainability amid the energy transition.
原油、绿色债券和碳市场之间的动态相互关系:来自模糊逻辑自编码器的证据
本文使用模糊逻辑自编码器(FLAE)模型,研究了2014年1月至2022年10月期间原油、绿色债券和碳排放等不同市场之间的动态相互关系,该模型提高了方法的复杂性,并有助于捕捉三个市场之间错综复杂的关系。FLAE的不同特征,如识别交叉滞后和引入新的s型激活函数,增强了结构的稳定性,并为研究跨市场的跨时间效应建立了模型。主要研究结果表明,绿色债券收益在中短期内对碳排放配额收益和布伦特原油收益产生负向影响。碳排放配额收益和石油收益对绿色债券收益预测的影响相对较小。预测绿色债券的回报主要是受其短期滞后的驱动。这些发现对能源市场的投资组合经理、有环保意识的投资者和能源转型期间关注金融可持续性的政策制定者都很有用。
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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来源期刊
Applied Soft Computing
Applied Soft Computing 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
6.90%
发文量
874
审稿时长
10.9 months
期刊介绍: Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.
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