NeuroCarbon EvoSNN: An Evolutionary Neuromorphic Deep Learning for Climate Policy Shock Propagation in Carbon Market

Carbon markets are strongly influenced by abrupt policy interventions that create asynchronous and nonlinear price shocks, which conventional deep learning models struggle to capture. This work introduces NeuroCarbon EvoSNN, an evolutionary neuromorphic framework that models policy events as spike-based representations to detect market shocks with low latency and high robustness. Evaluated on high-frequency EU ETS data, the approach significantly outperforms LSTM and Transformer baselines in detection speed, recall, and economic outcomes, demonstrating the effectiveness of neuromorphic deep learning for event-driven financial market analysis.