The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Stock market index prediction using deep Transformer model
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Citations
Cites
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568
Neural Machine Translation by Jointly Learning to Align and Translate
Bahdanau, D., Cho, K., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1409.0473 · Cited by 16,213
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
Mann, H. B., & Whitney, D. R. (1947) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177730491 · Cited by 14,320
Advances in Neural Information Processing Systems 29
Teymur, O., Zygalakis, K., & Calderhead, B. (2016) · Cited by 13,881
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., & Zhang, W. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i12.17325 · Cited by 7,752
Self-citationOn the Properties of Neural Machine Translation: Encoder–Decoder Approaches
Cho, K., van Merrienboer, B., Bahdanau, D., & Bengio, Y. (2014) · Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation · doi:10.3115/v1/w14-4012 · Cited by 7,099
Willmott, C., & Matsuura, K. (2005) · Climate Research · doi:10.3354/cr030079 · Cited by 6,512
Deep learning with long short-term memory networks for financial market predictions
Fischer, T., & Krauss, C. (2018) · European Journal of Operational Research · doi:10.1016/j.ejor.2017.11.054 · Cited by 2,785
Sharpe, W. F. (1994) · The Journal of Portfolio Management · doi:10.3905/jpm.1994.409501 · Cited by 2,534
(1998) · Springer Texts in Statistics · doi:10.1007/b98854 · Cited by 1,719
Cited by
Ren, J., Wang, A., Li, H., Yue, X., & Meng, L. (2023) · Sensors · doi:10.3390/s23146547 · Cited by 34
Metadata
- Authors
- Wang, C., Chen, Y., Zhang, S., & Zhang, Q.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2022-12
- Volume
- 208
- Pages
- 118128
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W4285402398
- Cited by
- 367
- References
- 41
- FWCI
- 41.56
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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- CoChat. (2026). Citation check: Stock market index prediction using deep Transformer model. https://app.cochat.ai/papers/10.1016/j.eswa.2022.118128
- The paper
- Wang, C., Chen, Y., Zhang, S., & Zhang, Q. (2022). Stock market index prediction using deep Transformer model. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2022.118128
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
