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Probabilities of transitions among endogenous regimes in asset returns and Environmental, Social and Governance scores
Business Strategy and the Environment ( IF 12.5 ) Pub Date : 2024-10-24 , DOI: 10.1002/bse.4011
Roy Cerqueti, Carmine Da Fermo, Marco Nicolosi

Assets' returns can be efficiently clustered in regimes, that are suitably defined non‐overlapping intervals creating a partition of the real numbers. This paper explores the relationship between the transition probabilities from one regime to another in assets' returns and the assets' MSCI Environmental, Social and Governance (ESG) scores. We apply the proposed methodology to the relevant empirical instance of the assets in the STOXX® Global 1800 Index. We consider three regimes—low, medium and high, on the basis of the variation range of the considered returns. Regimes are endogenous, in that their identification comes out from an entropy‐based optimization problem over the possible ranges of variation of the returns. We specifically investigate the possible linear relationship between transition probabilities among regimes and the ESG scores for different geographic regions, namely, America, Europe and Asia Pacific. The reference empirical period is the quadrennium 2018–2021. Results suggest that assets that are low ranked in ESG tend to remain in the low state of returns, if they are in the low state, while they tend to switch from higher to lower return states when the initial state is higher. On the other hand, assets that are highly ranked in the ESG dimensions, are likely to switch from a lower to a higher return state, when they are in a lower state or to remain in the same state when they are in a higher state. Results are more evident for America and Asia Pacific regions rather than Europe where regulation on ESG integration is at a more developed stage with respect to the other regions.

中文翻译:


资产回报和环境、社会和治理评分中内生制度之间转变的概率



资产的回报可以有效地聚集在制度中,这些制度是适当定义的非重叠区间,从而创建实数的分区。本文探讨了资产回报中从一种制度过渡到另一种制度的概率与资产的 MSCI 环境、社会和治理 (ESG) 评分之间的关系。我们将所提出的方法应用于 STOXX® 全球 1800 指数中资产的相关实证实例。我们根据所考虑回报的变化范围考虑三种制度——低、中和高。Regimes 是内生的,因为它们的识别来自基于熵的优化问题,该优化问题涉及可能的回报变化范围。我们专门研究了不同制度之间的转换概率与不同地理区域(即美洲、欧洲和亚太地区)的 ESG 分数之间可能存在的线性关系。参考实证期是 2018-2021 四年期。结果表明,在 ESG 中排名较低的资产如果处于低状态,则往往保持低回报状态,而当初始状态较高时,它们往往会从高回报状态切换到低回报状态。另一方面,在 ESG 维度中排名靠前的资产,当它们处于较低状态时,它们可能会从较低回报状态转变为较高回报状态,或者当它们处于较高状态时,它们可能会保持相同状态。美洲和亚太地区的结果更为明显,而不是欧洲,与其他地区相比,欧洲对 ESG 整合的监管处于更发达的阶段。
更新日期:2024-10-24
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