Traditional risk models often fall short in capturing the complex dynamics across multiple asset classes, regions, and liquidity profiles. Gain insights into:

• The development and implementation of functional, adaptable, data-driven risk models
• Cross-asset volatility, as well as fact and correlation modelling.
• Practical challenges in stress testing and scenario analysis.

Panel Questions:

• How can we develop and implement functional, adaptable, data-driven risk models that effectively capture the complexities across multiple asset classes, regions, and liquidity profiles?
• In the context of cross-asset volatility, what are the best practices for factor and correlation modeling to ensure accurate risk assessment and management?
• What are the practical challenges faced in conducting stress testing and scenario analysis, and how can these be addressed to improve risk model robustness?
• Given the dynamic nature of financial markets, how can risk models be designed to adapt to changing conditions and provide reliable insights during periods of market stress?