ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

주요 요인 위험 요소×신용 위험 모형 (Merton, KMV, CreditMetrics)×
분야재무학재무학
계열Regression modelRegression model
기원 연도19911974
창시자Litterman & Scheinkman (bond-return factors); Connor & Korajczyk (statistical APT factors)Robert C. Merton (structural model); J.P. Morgan / Gupton et al. (CreditMetrics)
유형Statistical factor model (dimension reduction)Structural and portfolio credit risk model
원전Litterman, R. & Scheinkman, J. (1991). Common Factors Affecting Bond Returns. Journal of Fixed Income, 1(1), 54-61. DOI ↗Merton, R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. The Journal of Finance, 29(2), 449-470. DOI ↗
별칭risk factor PCA, return covariance decomposition, statistical factor model, Risk Faktörü PCA (Getiri Kovaryans Ayrışımı)Merton model, KMV model, CreditMetrics, structural credit risk model
관련55
요약Risk 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.Credit risk models estimate the probability that a borrower defaults and the resulting distribution of credit losses. The structural approach was introduced by Robert C. Merton in 1974, treating a firm's equity as a call option on its assets, and was later extended into the KMV distance-to-default framework and the CreditMetrics rating-transition portfolio model published by J.P. Morgan in 1997.
ScholarGate데이터셋
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Principal Component Risk Factors · Credit Risk Models. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare