---
title: Hybrid Model for Index Futures Forecasting
url: https://www.ml-quant.com/papers/repec/eee-ecofin-v-69-y-2024-i-pb-s1062940823001456/
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:69:y:2024:i:pb:s1062940823001456
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1062940823001456%3Bh%3Drepec%3Aeee%3Aecofin%3Av%3A69%3Ay%3A2024%3Ai%3Apb%3As1062940823001456
featured: 2024-01-09
citations: unknown
topic: Econometrics & Forecasting
---


# Hybrid Model for Index Futures Forecasting

A new hybrid model called WT-ARIMA-LSTM has been introduced for share price index futures forecasting, offering superior accuracy and robust performance in various market conditions.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1062940823001456%3Bh%3Drepec%3Aeee%3Aecofin%3Av%3A69%3Ay%3A2024%3Ai%3Apb%3As1062940823001456
- Identifier: RePEc:eee:ecofin:v:69:y:2024:i:pb:s1062940823001456
- Released: 2024-01-09
- First featured: Quant Letter No. 32 (2024-01-09): https://www.ml-quant.com/issues/2024-01-09/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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