---
title: Machine learning in algorithmic investment strategies on global stock markets
url: https://www.ml-quant.com/papers/repec/eee-riibaf-v-66-y-2023-i-c-s0275531923001782/
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:riibaf:v:66:y:2023:i:c:s0275531923001782
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0275531923001782%3Bh%3Drepec%3Aeee%3Ariibaf%3Av%3A66%3Ay%3A2023%3Ai%3Ac%3As0275531923001782
featured: 2023-10-12
citations: unknown
topic: ML & AI Methods
---


# Machine learning in algorithmic investment strategies on global stock markets

Algorithmic investment strategies using machine learning models perform better than passive strategies, with Linear Support Vector Machine and Bayesian Generalized Linear Model being the most effective, research shows.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0275531923001782%3Bh%3Drepec%3Aeee%3Ariibaf%3Av%3A66%3Ay%3A2023%3Ai%3Ac%3As0275531923001782
- Identifier: RePEc:eee:riibaf:v:66:y:2023:i:c:s0275531923001782
- Released: 2023-10-12
- First featured: Quant Letter No. 20 (2023-10-12): https://www.ml-quant.com/issues/2023-10-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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