---
title: Mean-Variance Optimization with Affine GARCH
url: https://www.ml-quant.com/papers/repec/eee-finlet-v-59-y-2024-i-c-s1544612323011212/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323011212
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1544612323011212%3Bh%3Drepec%3Aeee%3Afinlet%3Av%3A59%3Ay%3A2024%3Ai%3Ac%3As1544612323011212
featured: 2024-01-09
citations: unknown
topic: Portfolio & Allocation
---


# Mean-Variance Optimization with Affine GARCH

The study shows that Affine GARCH models are more efficient in portfolio optimization compared to homoscedastic variants.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1544612323011212%3Bh%3Drepec%3Aeee%3Afinlet%3Av%3A59%3Ay%3A2024%3Ai%3Ac%3As1544612323011212
- Identifier: RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323011212
- Released: 2024-01-09
- First featured: Quant Letter No. 32 (2024-01-09): https://www.ml-quant.com/issues/2024-01-09/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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