Flexible Target Prediction for Quantitative Trading in the American Stock Market: A Hybrid Framework Integrating Ensemble Models, Fusion Models and Transfer Learning.
- DOI
- 10.3390/e28010084
- Published
- 2026 Jan 11
- Container
- Entropy (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3390/e28010084,
title = {Flexible Target Prediction for Quantitative Trading in the American Stock Market: A Hybrid Framework Integrating Ensemble Models, Fusion Models and Transfer Learning.},
author = {Yan K and Yue Z and Wu CC and He Q and Zhou J and Hao Z and Li Y},
year = {2026},
journal = {Entropy (Basel, Switzerland)},
doi = {10.3390/e28010084},
url = {https://doi.org/10.3390/e28010084}
}RIS
TY - JOUR TI - Flexible Target Prediction for Quantitative Trading in the American Stock Market: A Hybrid Framework Integrating Ensemble Models, Fusion Models and Transfer Learning. AU - Yan K AU - Yue Z AU - Wu CC AU - He Q AU - Zhou J AU - Hao Z AU - Li Y PY - 2026 JO - Entropy (Basel, Switzerland) DO - 10.3390/e28010084 UR - https://doi.org/10.3390/e28010084 ER -
APA
K, Y., Z, Y., CC, W., Q, H., J, Z., Z, H., & Y, L. (2026). Flexible Target Prediction for Quantitative Trading in the American Stock Market: A Hybrid Framework Integrating Ensemble Models, Fusion Models and Transfer Learning.. Entropy (Basel, Switzerland). https://doi.org/10.3390/e28010084
Source records
- pubmed · retrieved 2026-09-25T18:47:24.015Z
- europe-pmc · retrieved 2026-09-25T18:47:24.108Z