Abstract:
In recent years, people around the world have expressed their concerns regarding the environment and society and the concept of sustainable development has expanded considerably. One way to contribute to sustainable development is to encourage individuals and institutional investors to make investment choices aimed at rewarding companies engaged in the management of environmental and social impact and committed to improving their corporate governance. For this reason, sustainable finance has born. The prevailing approach to Sustainable and Responsible Investing (SRI) is the integration of Environmental, Social and Governance (ESG) factors into financial analysis, which can improve the risk-return profile of investments. This master thesis is a further contribution to the existing studies on the performance of ESG portfolios. First, companies included in the S&P 100 were ranked based on their ESG scores, which were provided by Refinitiv, one of the largest providers of financial data. The next step was the creation of “bottom” portfolios, consisting of the 20 low-ranked stocks and “top” portfolios, composed by the 20 high-ranked stocks. Then, long-short portfolios were constructed, by holding a long position in high-rated portfolios and a short position in low-rated portfolios. The analysis was carried out using the multi-factor models of Fama and French and discusses the possible significant differences in the performance and risk exposure between low-rated and high-rated portfolios. Thanks to this research, it has been possible to identify which portfolios perform best in the timeframe July 2003-June 2020, offering a brief insight into the effects of the COVID-19 pandemic on the financial performance of sustainable and responsible investments too.
