Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель портфеля Блэка-Литтермана× | Регрессия методом обыкновенных наименьших квадратов (ОНМК)× | |
|---|---|---|
| Область≠ | Финансы | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1992 | 2019 |
| Автор метода≠ | Fischer Black & Robert Litterman | Wooldridge (textbook treatment); classical least squares |
| Тип≠ | Bayesian portfolio allocation model | Linear regression |
| Основополагающий источник≠ | Black, F. & Litterman, R. (1992). Global Portfolio Optimization. Financial Analysts Journal, 48(5), 28-43. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Другие названия≠ | Black-Litterman, BL model, Black-Litterman Portföy Modeli | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Связанные | 5 | 5 |
| Сводка≠ | The Black-Litterman model, introduced by Fischer Black and Robert Litterman in 1992, is a Bayesian portfolio allocation framework that blends market-equilibrium returns with an investor's own views to produce more stable, intuitive portfolios. It was designed to cure the extreme concentration and input sensitivity of classical Markowitz mean-variance optimisation. | 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). |
| ScholarGateНабор данных ↗ |
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