Záznam dôkazov metódy

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.

Sources recorded, not reviewed

Zdrojový záznam

Citácie skopírované doslovne zo zdrojového záznamu metódy. Nevyplýva z nich žiadne overenie na úrovni tvrdenia.

Risk Factor PCA via Return Covariance Decomposition

Taxonomický záznam metódy · regression-model / finance

Otvoriť celú metódu

Spracované tvrdenia

Tvrdenia uložené v registri dôkazov, každé s vlastným hodnotením.

Zatiaľ žiadne spracované tvrdenia

Tento pohľad nevymýšľa hodnotenie tvrdenia, ak register žiadne nemá.

Súvisiace metódy

Vygenerované z grafu metód a zobrazené ako vzťahy navrhnuté strojom – nevyplýva z nich žiadne tvrdenie o dôkaze.

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.