---
title: Multiperiod Portfolio Allocation
url: https://www.ml-quant.com/papers/repec/eee-ecofin-v-68-y-2023-i-c-s1062940823001201/
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:ecofin:v:68:y:2023:i:c:s1062940823001201
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1062940823001201%3Bh%3Drepec%3Aeee%3Aecofin%3Av%3A68%3Ay%3A2023%3Ai%3Ac%3As1062940823001201
featured: 2023-10-18
citations: unknown
topic: Portfolio & Allocation
---


# Multiperiod Portfolio Allocation

The research finds that considering volatility clustering reduces hedging demands in dynamic multiperiod portfolio choices, while non-normalities have minor effects on allocations.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1062940823001201%3Bh%3Drepec%3Aeee%3Aecofin%3Av%3A68%3Ay%3A2023%3Ai%3Ac%3As1062940823001201
- Identifier: RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823001201
- Released: 2023-10-18
- First featured: Quant Letter No. 22 (2023-10-18): https://www.ml-quant.com/issues/2023-10-18/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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