January 16, 2025
15.00-17.00
Department of Mathematics- Saleri room- VI floor
Tiziano De Angelis (Università di Torino)
A model of strategic sustainable investment
We study a problem of optimal irreversible investment and emission reduction formulated as a nonzero-sum dynamic game between an investor with environmental preferences and a firm. The game is set in continuous time on an infinite-time horizon. The firm generates profits with a stochastic dynamics and may spend part of its revenues towards emission reduction (e.g., renovating the infrastructure). The firm’s objective is to maximize the discounted expectation of a function of its profits. The investor participates in the profits and may decide to invest to support the firm’s production capacity. The investor uses a profit function which accounts for both financial and environmental factors. Nash equilibria of the game are obtained via a system of variational inequalities. We formulate a general verification theorem for this system in a diffusive setup and construct an explicit solution in the zero-noise limit. Our explicit results and numerical approximations show that both the investor’s and the firm’s optimal actions are triggered by moving boundaries that increase with the total amount of emission abatement.
Joint work with C.C. Rodrigues Graciani (Scuola Superiore Meridionale) and P. Tankov (ENSAE)
Discussant: Alessandro Calvia (Politecnico di Milano)
Sandra Paterlini (Università di Trento)
Chasing ESG performance: How Methodologies Shape Outcomes
ESG metrics play a crucial role in sustainable finance but face growing criticism for their inability to accurately capture true sustainability improvements. This study investigates how methodological choices can introduce distortions in ESG scores, with a primary focus on Refinitiv ESG data, while offering insights applicable to other providers as well. We show that methodological choices, such as score normalization, significantly impact the ability of scores to reflect genuine sustainability progress. Specifically, the inclusion of new, lower-performing entrants can artificially inflate the scores of top-ranked companies, obscuring actual improvements by relying on peer comparisons. Moreover, our analysis reveals that once companies achieve an A-rating category, they are unlikely to be downgraded, further highlighting the impact of these methodological decisions on the dynamics of ESG scoring. Analyzing data from three key sectors over the period 2012–2021 reveals that less than 45% of total score variation is attributable to company disclosures, underscoring the influence of score construction methodologies. By constructing a much simpler aggregation method, we demonstrate strong correlation with Refinitiv’s scores while reducing distortions from new entrants and peer effects, offering a more transparent and representative measure of sustainability performance.
Joint work with Matteo Benuzzi, Karoline Bax and Emanuele Taufer
Discussant: Michele Azzone (Politecnico di Milano)
This event has been partially supported by MUR, Department of Excellence 2023-27
