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Principal Component Risk Factors

Risk Factor PCA is a dimension-reduction method that decomposes the return covariance matrix of many assets into a small set of orthogonal principal components interpreted as systematic risk factors. Litterman and Scheinkman (1991) used it to show that bond returns are driven by a few common factors, and Connor and Korajczyk (1988) developed the statistical-factor interpretation for the APT.

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Risk Factor PCA via Return Covariance Decomposition

Rekod kaedah taksonomik · regression-model / finance

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Same method familyCredit Risk Modelsmachine-suggested · Relational suggestion, not evidence.See alsoFactor Analysismachine-suggested · Relational suggestion, not evidence.Same method familyInterest Rate Modelsmachine-suggested · Relational suggestion, not evidence.Same method familyMean-Variance Portfolio Optimizationmachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.