A0361
Title: Robust selection with carbon penalty
Authors: Immacolata Oliva - Sapienza University of Rome (Italy)
Ilaria Stefani - University of Parma (Italy) [presenting]
Abstract: The aim is to present a robust, dynamic optimization model for continuous-time portfolio allocation, considering an investor with access to both green and brown assets in the stock market. It is assumed that the stock price dynamics are governed by a stochastic volatility model, where the instantaneous precision is modeled. The concept of 'penalized wealth' is introduced, where the wealth of an investor is adjusted for the losses incurred when investing in brown assets, which are assumed to bear higher risks, with the penalty being dependent on a parameter related to carbon emissions. By solving a system of ordinary differential equations (ODEs), a closed-form solution is derived to the optimization problem. Theoretical results highlight the significant influence of ambiguity aversion parameters on optimal policies. Furthermore, the parameter governing carbon emissions acts as an additional risk aversion, so the higher the emissions, the lower the portfolio allocation in the asset brown. A comprehensive numerical analysis, conducted with real data, validates these findings. Finally, the importance of ambiguity aversion is emphasized in investment decisions, particularly in the context of environmental sustainability and climate-related financial risks.
