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Фактори на риска чрез главни компоненти×Оптимизация на портфейл по средна стойност и дисперсия (Марковиц)×
ОбластФинансиФинанси
СемействоRegression modelRegression model
Година на възникване19911952
СъздателLitterman & Scheinkman (bond-return factors); Connor & Korajczyk (statistical APT factors)Harry Markowitz
ТипStatistical factor model (dimension reduction)Mean-variance optimization model
Основополагащ източникLitterman, R. & Scheinkman, J. (1991). Common Factors Affecting Bond Returns. Journal of Fixed Income, 1(1), 54-61. DOI ↗Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91. DOI ↗
Други названияrisk factor PCA, return covariance decomposition, statistical factor model, Risk Faktörü PCA (Getiri Kovaryans Ayrışımı)Markowitz portfolio theory, modern portfolio theory, efficient frontier optimization, Ortalama-Varyans Portföy Optimizasyonu (Markowitz)
Свързани55
РезюмеRisk 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.Mean-variance portfolio optimization is the foundational model of modern portfolio theory, introduced by Harry Markowitz in 1952. It describes portfolios in an expected-return versus risk (variance) plane and traces the efficient frontier of allocations that offer the highest expected return for each level of risk, covering the minimum-variance portfolio, the maximum-Sharpe-ratio portfolio, and constrained variants.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Principal Component Risk Factors · Mean-Variance Portfolio Optimization. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare