Abstract
Background: Climate-related physical and transition risks introduce novel nonlinearities, jumps and regime shifts into asset dynamics that standard derivative models do not capture, creating gaps in pricing and hedging practice (Battiston et al., 2021; Karydas & Xepapadeas, 2022). This paper proposes a compact research design for novel derivative instruments tailored to climate exposures and for robust hedging protocols. Methods: We outline a hybrid modelling framework that combines scenario-conditioned stochastic processes (regime-switching jump-diffusions) calibrated to climate scenario outputs (Holden et al., 2024; Broeders et al., 2023) with robust optimization and model-uncertainty-aware hedging (Assa & Gospodinov, 2017). Pricing employs risk-adjusted discounting and market-implied scenario weights; hedging uses dynamic strategies evaluated by CVaR and stress-scenario replication performance (DINH & Gong, 2024; Liu, 2023). Results: The planned analyses report pricing sensitivities across transition/physical scenario states, hedge slippage under parameter misspecification, and cost-benefit comparisons versus standard instruments. Expected findings include non-linear premium loading for jump and regime risks, improved downside protection from purpose-built climate derivatives, and hedge effectiveness that degrades asymmetrically under extreme scenarios (Agliardi & Agliardi, 2021; Campiglio et al., 2022). Conclusions: The proposed IMRaD study provides actionable templates for issuers, risk managers and regulators to price and hedge climate risks using novel derivatives, highlighting the need for scenario-based calibration, robustness to model error, and clear accounting/treatment consistent with established hedging guidance (Drakopoulou, 2014). The plan supports empirical implementation and extension to market design and regulatory implications.