Work

Investing in sustainability during the Covid-19 pandemic: evidence for french mutual funds

Year: 2023
Type: dissertation
Abstract: The purpose of this dissertation is to study the performance of French mutual funds with a geographical focus in Europe. To do so, two performance evaluation models were used: the Fama and French (2015) 5-factor, and the Fama and French (2018) 6-factor models. The performance of funds is first evaluated from January 2010 to July 2022 using these models in a conditional setting. Afterwards we focus on two different subperiods: One before the Covid-19 outbreak, from August 2017 to January 2020, and another one post Covid, from February 2020 to July 2022. A dummy variable was added to the models to distinguish performance and risk between subperiods. Performance is investigated across different criterion of sustainability, namely the Sustainable Finance Disclosure Regulation (SFDR) categorization, the French Socially Responsible Investment (SRI) label, and Refinitiv ESG, Environmental and Emissions scores. Furthermore, we analyse mutual funds’ flows, first around the Covid-19, and second around the publication date of the SFDR. The dataset used in the performance evaluation over the longer timespan includes 303 mutual funds, while the one used in the Covid-19 analysis includes 309 mutual funds, from which we form equally and value weighted portfolios. The results show that, in general, there are no financial gains in investing in these mutual funds. Nonetheless, when comparing performance across different levels of sustainability, more sustainable funds exhibit neutral or outperformance relative to less sustainable funds. In all, the pandemic did not influence performance in a statistically significant manner. In relation to fund flows analysis, the overall results show a higher increase of fund flows towards more sustainable funds, namely funds with the SFDR categorization of article 9 and article 8 and SRI labelled funds, being this prioritization from the investors side more evident after the Covid-19 crash.
Language: English
Subfield: Finance
Open Access status: green
OpenAlex ID: W6991861586
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