ScholarGate
Βοηθός

Σύγκριση μεθόδων

Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.

Παράγοντες Κινδύνου Κύριων Συνιστωσών×Παλινδρόμηση Ελαχίστων Τετραγώνων (OLS)×
ΠεδίοΧρηματοοικονομικάΟικονομετρία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης19912019
ΔημιουργόςLitterman & Scheinkman (bond-return factors); Connor & Korajczyk (statistical APT factors)Wooldridge (textbook treatment); classical least squares
ΤύποςStatistical factor model (dimension reduction)Linear regression
Θεμελιώδης πηγήLitterman, R. & Scheinkman, J. (1991). Common Factors Affecting Bond Returns. Journal of Fixed Income, 1(1), 54-61. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Εναλλακτικές ονομασίεςrisk factor PCA, return covariance decomposition, statistical factor model, Risk Faktörü PCA (Getiri Kovaryans Ayrışımı)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Συναφείς55
ΣύνοψηRisk 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
ScholarGateΣύνολο δεδομένων
  1. v1
  2. 2 Πηγές
  3. PUBLISHED
  1. v1
  2. 1 Πηγές
  3. PUBLISHED

Μετάβαση στην αναζήτηση Λήψη διαφανειών

ScholarGateΣύγκριση μεθόδων: Principal Component Risk Factors · OLS Regression. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare