Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Portfolio modela "Black-Litterman"× | Riska mēri astē (paredzamais trūkums, spektrālie, ekspektiles)× | |
|---|---|---|
| Nozare | Finanses | Finanses |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1992 | 1999 |
| Autors≠ | Fischer Black & Robert Litterman | Artzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall) |
| Tips≠ | Bayesian portfolio allocation model | Coherent tail risk measure |
| Pirmavots≠ | Black, F. & Litterman, R. (1992). Global Portfolio Optimization. Financial Analysts Journal, 48(5), 28-43. DOI ↗ | Artzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗ |
| Citi nosaukumi≠ | Black-Litterman, BL model, Black-Litterman Portföy Modeli | expected shortfall, conditional value at risk, CVaR, spectral risk measure |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | Tail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it. |
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