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主成分风险因子×均值-方差投资组合优化(Markowitz)×
领域金融学金融学
方法族Regression modelRegression model
起源年份19911952
提出者Litterman & Scheinkman (bond-return factors); Connor & Korajczyk (statistical APT factors)Harry Markowitz
类型Statistical factor model (dimension reduction)Mean-variance optimization model
开创性文献Litterman, 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 ↗
别名risk 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)
相关55
摘要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.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.
ScholarGate数据集
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  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: Principal Component Risk Factors · Mean-Variance Portfolio Optimization. 于 2026-06-18 检索自 https://scholargate.app/zh/compare