---
title: Portfolio Optimization Clustering
url: https://www.ml-quant.com/papers/repec/eee-ecosta-v-32-y-2024-i-c-p-1-16/
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:ecosta:v:32:y:2024:i:c:p:1-16
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2452306221001416%3Bh%3Drepec%3Aeee%3Aecosta%3Av%3A32%3Ay%3A2024%3Ai%3Ac%3Ap%3A1-16
featured: 2024-11-06
citations: unknown
topic: Portfolio & Allocation
---


# Portfolio Optimization Clustering

The article suggests a new investment strategy using clustering techniques to minimize assets in a portfolio, potentially outperforming traditional equal weight portfolios.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2452306221001416%3Bh%3Drepec%3Aeee%3Aecosta%3Av%3A32%3Ay%3A2024%3Ai%3Ac%3Ap%3A1-16
- Identifier: RePEc:eee:ecosta:v:32:y:2024:i:c:p:1-16
- Released: 2024-11-06
- First featured: Quant Letter No. 73 (2024-11-06): https://www.ml-quant.com/issues/2024-11-06/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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