Ultimate access to all questions.
Explanation:
Regression hedging enhances the flexibility and precision of hedging strategies by employing slope coefficients from historical yield regressions as risk weights. This allows a tailored approach that adjusts the hedge according to actual past correlations rather than relying on averaged or static assumptions like DV01-neutral hedges.
B is incorrect. It does not rely solely on current forecasts but integrates extensive historical yield data.
C is incorrect. Risk weights in regression hedging are dynamic rather than static.
D is incorrect. Historical correlations are essential to determine slope-based risk weights in regression hedges.
Things to Remember:
No comments yet.
Q.6505 An investment fund is considering using regression hedging to enhance its current DV01-neutral strategy. How does regression hedging offer greater flexibility and precision compared to a DV01-neutral hedge, particularly concerning the risk weights assigned?
A
Risk weight is adaptable, derived from slope coefficients, offering tailored strategies.
B
It adjusts dynamically based on recent market mood forecasts.
C
The risk weight in a regression hedge is fixed and determined at inception.
D
Regression hedge risk weight requires no historical data correlation.