---
title: Forecasting FTSE Bursa Malaysia
url: https://www.ml-quant.com/papers/repec/rnd-arimbr-v-16-y-2024-i-2-p-104-114/
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:rnd:arimbr:v:16:y:2024:i:2:p:104-114
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fojs.amhinternational.com%2Findex.php%2Fimbr%2Farticle%2Fview%2F3773%2F2471%3Bh%3Drepec%3Arnd%3Aarimbr%3Av%3A16%3Ay%3A2024%3Ai%3A2%3Ap%3A104-114
featured: 2024-08-28
citations: unknown
topic: Econometrics & Forecasting
---


# Forecasting FTSE Bursa Malaysia

The study uses machine learning to predict stock prices in Malaysia, finding the Sequential Minimal Optimization Regression algorithm to be most accurate.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fojs.amhinternational.com%2Findex.php%2Fimbr%2Farticle%2Fview%2F3773%2F2471%3Bh%3Drepec%3Arnd%3Aarimbr%3Av%3A16%3Ay%3A2024%3Ai%3A2%3Ap%3A104-114
- Identifier: RePEc:rnd:arimbr:v:16:y:2024:i:2:p:104-114
- Released: 2024-08-28
- First featured: Quant Letter No. 63 (2024-08-28): https://www.ml-quant.com/issues/2024-08-28/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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