What type of model combines historical simulation with conditional volatility?

The Filtered Historical Simulation Model is designed to integrate elements of historical simulation with the concept of conditional volatility. This model employs historical data to estimate potential future losses, while also adjusting for current market conditions and volatility trends. By applying a conditional volatility approach, it allows for a better representation of changing market dynamics as it focuses on recent data trends and their impact on future risk assessments.

Using historical simulations alone may not adequately capture the changing nature of volatility, particularly during turbulent market periods. The Filtered Historical Simulation Model addresses this limitation by filtering the historical returns to reflect more recent volatility estimates, thus producing a more adaptive and relevant risk assessment.

This model effectively combines the strengths of historical data, which provides a robust empirical basis for risk estimation, with the adaptability of conditional measures of volatility, allowing for a more accurate and responsive evaluation of market risk.