Decision Analytics Journal · 2026
A predictive analytics approach for forecasting global stock index returns using deep learning techniques
Research overview
A comparison of LSTM, dual-layer LSTM, and Transformer models for returns across five major global stock indices, combining technical and fundamental inputs.
Earlier preprint
Hu, Liang, and Shen, Yinru. Hybrid Machine Learning Models for Predicting Relative Returns of Five Major Global Stock Indices. Research Square, version 1, posted August 30, 2024. Preprint · DOI: 10.21203/rs.3.rs-4818027/v1.
The preprint is listed here alongside the journal article as part of the same research record.
Venue rankings & metrics
Decision Analytics Journal · Sources checked October 5, 2026
- SJRQ12025
Q1 in Analysis, Applied Mathematics, Decision Sciences (miscellaneous), and Modeling and Simulation, 2025.
SCImago · Decision Analytics Journal ↗- SJR1.6862025
SCImago Journal Rank indicator, 2025.
SCImago · Decision Analytics Journal ↗
SJR Q1 refers to SCImago's 2025 subject categories, not a JCR or CAS classification. Only source-verified metrics are displayed.
Citation · BibTeX
@article{hu2026globalreturns,
title = {A predictive analytics approach for forecasting global stock index returns using deep learning techniques},
author = {Hu, Liang and Shen, Yinru},
journal = {Decision Analytics Journal},
volume = {18},
pages = {100685},
year = {2026},
doi = {10.1016/j.dajour.2026.100685}
}