Macroeconomic Modelling of Climate Value-at-Risk and Capital Adequacy

This paper presents a macroeconomic approach to calculating Climate Value-at-Risk (CliVaR) for financial institutions, addressing critical limitations in existing commercial solutions and historical data availability. This methodology leverages the Network for Greening the Financial System (NGFS) scenarios to derive implied forward-looking means and volatilities from scenarios mapped to macroeconomic variables (MEVs), circumventing the reliance on insufficient historical data. Through regression analysis, we identify statistically significant relationships between climate-sensitive macroeconomic variables and bank equity values, based on the premise that climate risk is transmitted to bank balance sheets via its impact on the general economy. It is recognised that MEVs alone cannot explain the full variance in equity values and the regression of MEVs to equity is inherently inefficient. However, the purpose of the regression is to determine statistically significant MEVs and not to predict the share price. Along with the NGFS scenarios, this enables the Monte Carlo simulation and the calculation of CliVaR. To account for the regression inefficiency, a Post-Model Adjustment (PMA) equation is developed. The methodology is demonstrated in a practical case study, by calculating a CliVaR based climate risk Pillar 2A capital requirement for Standard Bank Group. This proof-of-concept demonstrates the feasibility of transparent, in-house CliVaR calculations.