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Explanation:
Principal Component Analysis (PCA) is a dimensionality reduction technique widely used in fixed-income portfolio management. Its primary advantage is that it decomposes complex, correlated yield curve movements into a small number of uncorrelated principal components (typically interpreted as shift, twist, and butterfly movements). These components capture the vast majority of the variance in interest rates, allowing risk managers to identify and hedge exposures efficiently without assuming perfect correlation.
Q.68 A financial analyst is exploring principal component analysis (PCA) for constructing a hedging portfolio. What primary advantage does PCA offer when identifying risk exposures within a portfolio of fixed-income instruments?
A
PCA assumes perfect correlation across all rates, simplifying analysis.
B
PCA assumes perfect correlation across all rates, simplifying analysis.
C
PCA guarantees a constant yield curve slope, assisting consistent interpretations.
D
PCA decomposes the yield curve changes into uncorrelated components that capture the most variance.
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