混合广义正态分布和EGARCH模型来分析ESG和传统投资的回报和波动性

IF 1.4 4区 数学 Q2 STATISTICS & PROBABILITY Asta-Advances in Statistical Analysis Pub Date : 2023-11-18 DOI:10.1007/s10182-023-00487-7
Pierdomenico Duttilo, Stefano Antonio Gattone, Barbara Iannone
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摘要

环境、社会和治理(ESG)标准日益融入投资过程,有助于克服全球可持续性挑战。本文着眼于对动荡时期的反应,分析了2016年至2022年几个ESG指数的回报和波动性,并与传统指数进行了比较。这些指数包括以下市场:全球、美国、欧洲和新兴市场。首先,利用广义正态分布的双成分混合,利用Naïve贝叶斯分类器客观地检测金融市场动荡时期。其次,采用外生虚拟变量的EGARCH-in-mean模型来捕捉动荡时期的影响。结果表明,收益和波动率都受到动荡时期的影响。不同指数类型和市场的回报风险表现不同:欧洲ESG指数的波动率低于其传统市场基准,而在其他市场,估计的波动率大致相同。此外,ESG指数与非ESG指数在动荡期影响、风险溢价和杠杆效应方面存在差异。
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Mixtures of generalized normal distributions and EGARCH models to analyse returns and volatility of ESG and traditional investments

Environmental, social and governance (ESG) criteria are increasingly integrated into investment process to contribute to overcoming global sustainability challenges. Focusing on the reaction to turmoil periods, this work analyses returns and volatility of several ESG indices and makes a comparison with their traditional counterparts from 2016 to 2022. These indices comprise the following markets: Global, the US, Europe and emerging markets. Firstly, the two-component mixture of generalized normal distribution was exploited to objectively detect financial market turmoil periods with the Naïve Bayes’ classifier. Secondly, the EGARCH-in-mean model with exogenous dummy variables was applied to capture the turmoil period impact. Results show that returns and volatility are both affected by turmoil periods. The return–risk performance differs by index type and market: the European ESG index is less volatile than its traditional market benchmark, while in the other markets, the estimated volatility is approximately the same. Moreover, ESG and non-ESG indices differ in terms of turmoil periods impact, risk premium and leverage effect.

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来源期刊
Asta-Advances in Statistical Analysis
Asta-Advances in Statistical Analysis 数学-统计学与概率论
CiteScore
2.20
自引率
14.30%
发文量
39
审稿时长
>12 weeks
期刊介绍: AStA - Advances in Statistical Analysis, a journal of the German Statistical Society, is published quarterly and presents original contributions on statistical methods and applications and review articles.
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