Ricerc@Sapienza

This research project deals with the challenge of developing new Key Performance Indicators (KPI) to assess the companies¿ Corporate Social Responsibility (CSR) explained as a function of Socially Responsible Investments (SRI), also known as Environmental, Social and Corporate Governance (ESG) investments. The recent attention to SRI has become crucial for regulators and governments whose directives focus on sustainable investments to generate sustainable growth. In this context, Europe has set important international agreements and investments in ¿green¿ projects. Therefore, the identification and evaluation of the degree of responsibility represents a research question of interest also for investors.
Rating agencies introduced sustainability rating based on firms' ESG business model that account for specific features such as emissions, environmental product innovations, human rights, and the companies' structure. Measuring the risk profiles of SRI becomes crucial for guidance and benchmarking. However, there is not a unified framework for ESG ratings and their reliability is strongly criticized calling for the identification of suitable KPI able to express the real impact of SRI on the firms¿ performances.
The aim of this project is twofold. First, we propose to build new KPI to assess sustainable investments using structural information on the company¿s business model as well as using balance sheet data. The KPI will be built with tree-based machine learning algorithms that detect hidden relationships and describe potential complex patterns while preserving the interpretability property. The second aim is to analyze the relationship between KPI and the main financial risks, such as market and credit risks. Market risk will be measured using companies¿ performances in terms of stocks¿ return conditional volatility whereas the impact of the KPI on credit risk is related to the firms¿ probability of default computed as an extension of the Altman¿s Z score.