Explanation:
Filtered Historical Simulation (FHS) typically employs GARCH-family models to standardize historical returns and update current volatilities. These models inherently accommodate volatility clustering, and depending on the specific model used (e.g., asymmetric GARCH variants like EGARCH or GJR-GARCH), they allow positive and negative returns to impact future volatility differently. Age-weighted HS uses an exponential decay, not linear. Volatility-weighted HS scales returns by the ratio of current to historical volatility.
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A
The correlation-weighted HS approach adjusts the return observations by multiplying each return by the current correlation divided by the historical correlation.
B
The filtered HS approach accommodates volatility clustering and allows positive and negative returns to impact volatility differently.
C
The volatility-weighted HS approach adjusts returns upward when the current volatility is below the long-term average volatility.
D
The age-weighted HS approach assumes that the value of the information contained in a return observation declines in a linear manner starting from the date it is first observed.