Bayesian Tail Risk Forecasting with Geopolitical Narratives and Range-Based Volatility

Key Points

• The forecast improves tail risk prediction by incorporating geopolitical narratives, leading to more accurate projections.
• Key evidence includes a statistically significant enhancement in forecasting performance during volatile market periods.
• Bayesian methods are utilized for analyzing risk and volatility, emphasizing the importance of narrative context.
• The findings highlight the potential of integrating qualitative data into quantitative forecasting models for better risk assessment.