Bayesian Learning in an Affine GARCH Model with Application to Portfolio Optimization
This paper develops a methodology to accommodate uncertainty in a GARCH model with the goal of improving portfolio decisions via Bayesian learning. Given the abundant evidence of uncertainty in estimating expected returns, we focus our analyses on the single parameter driving expected returns. After...
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| Hauptverfasser: | , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI AG
2024-05-01
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| Schriftenreihe: | Mathematics |
| Schlagworte: | |
| Online-Zugang: | https://www.mdpi.com/2227-7390/12/11/1611 |
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