Researchers Katia Colaneri, Federico D’Amario, and Daniele Mancinelli, affiliated with the University of Rome Tor Vergata, have published a study titled “Carbon-Penalised Portfolio Insurance Strategies in a Stochastic Factor Model with Partial Information” in the Journal of Economic Dynamics and Control. Their work explores how investors can manage portfolios to reduce carbon footprints while maintaining financial performance.
The study focuses on proportional portfolio insurance (PPI) strategies, which help investors limit downside risk while still allowing for potential gains. The researchers aim to determine the best PPI strategy that maximizes the expected utility of the terminal cushion—the difference between the portfolio value and a predetermined minimum level. This cushion is penalized based on the realized volatility of stocks from carbon-intensive sectors, effectively discouraging investments in high-carbon assets.
The team models the dynamics of risky assets using geometric Brownian motions, where the drift rates are influenced by an unobservable common stochastic factor. This factor represents market-specific or economy-wide variables that are not directly observable. Using stochastic filtering theory, they formulate and solve an optimization problem for a constant relative risk aversion (CRRA) utility function. They characterize optimal carbon-penalized PPI strategies and value functions under both full and partial information scenarios, quantifying the utility loss due to incomplete information.
Through numerical analysis, the researchers demonstrate that their proposed strategy can reduce carbon emission intensity without sacrificing financial performance. This finding is significant for the energy sector, as it provides a framework for investors to align their portfolios with environmental goals while maintaining competitive returns. The study offers practical insights for energy companies and investors looking to integrate carbon footprint considerations into their investment strategies, potentially driving more sustainable practices within the industry.
The research was published in the Journal of Economic Dynamics and Control, a peer-reviewed academic journal that focuses on economic theory, econometrics, and quantitative economics.
This article is based on research available at arXiv.