Exploiting the low-risk anomaly using machine learning to enhance the Black-Litterman framework : evidence from South Korea
Sujin Pyo, Jaewook Lee
| Year of publication: |
2018
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|---|---|
| Authors: | Pyo, Sujin ; Lee, Jaewook |
| Published in: |
Pacific-Basin finance journal. - Amsterdam [u.a.] : Elsevier, ISSN 0927-538X, ZDB-ID 1343420-2. - Vol. 51.2018, p. 1-12
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| Subject: | Low-risk anomaly | Machine learning models | Low beta | The Black-Litterman model | Volatility prediction | Künstliche Intelligenz | Artificial intelligence | Südkorea | South Korea | CAPM | Prognoseverfahren | Forecasting model | Volatilität | Volatility | Portfolio-Management | Portfolio selection | Schätzung | Estimation |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.pacfin.2018.06.002 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012035052