Skip to content

FRM Part II · FRM Exam Part II · Regression Hedging and Principal Component Analysis

A portfolio manager hedges a bond position using a regression of yield changes on a hedging instrument's yield changes. The regression has a high beta but a low R-squared of 0.15. Which conclusion is most appropriate?

The hedge leaves substantial residual or basis risk. An R-squared of 0.15 means the hedging instrument explains only 15% of the variation in the position's yield changes, so most variance remains unhedged even if beta is high.

  1. AThe hedge ratio is unbiased, so residual risk is negligible
  2. BThe hedge will remove most variance because beta is high
  3. CThe hedge is reliable because R-squared measures only the intercept
  4. DThe hedge leaves substantial residual (basis) risk because the instrument explains little of the yield variationCorrect

Explanation

R-squared of 0.15 means only 15% of variance is explained, so about 85% remains as unhedged residual risk regardless of beta size. Beta sets the hedge ratio, not its effectiveness.

Did you get it right without looking?

One question tells you little. A timed set on Regression Hedging and Principal Component Analysis shows your real accuracy, how long you take and where you lose marks.

Practise Regression Hedging and Principal Component AnalysisFree diagnostic mock

More Regression Hedging and Principal Component Analysis questions