---
title: Forecasting S&P 500 returns with ML
url: https://www.ml-quant.com/papers/repec/spr-fininn-v-10-y-2024-i-1-d-10-1186-s40854-024-00644-0/
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:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-024-00644-0
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1186%2Fs40854-024-00644-0%3Bh%3Drepec%3Aspr%3Afininn%3Av%3A10%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1186_s40854-024-00644-0
featured: 2024-04-24
citations: unknown
topic: Econometrics & Forecasting
---


# Forecasting S&P 500 returns with ML

The LSTM classifier, a machine learning technique, can predict future stock prices more accurately than random choice, questioning the random walk and efficient market theories.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1186%2Fs40854-024-00644-0%3Bh%3Drepec%3Aspr%3Afininn%3Av%3A10%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1186_s40854-024-00644-0
- Identifier: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-024-00644-0
- Released: 2024-04-24
- First featured: Quant Letter No. 46 (2024-04-24): https://www.ml-quant.com/issues/2024-04-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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