Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets
- DOI
- 10.3390/app142411897
- Published
- 12
- Container
- Applied Sciences
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/app142411897,
title = {Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets},
author = {Michał Wawer and Jarosław A. Chudziak and Ewa Niewiadomska-Szynkiewicz},
year = {2024},
journal = {Applied Sciences},
doi = {10.3390/app142411897},
url = {https://doi.org/10.3390/app142411897}
}RIS
TY - JOUR TI - Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets AU - Michał Wawer AU - Jarosław A. Chudziak AU - Ewa Niewiadomska-Szynkiewicz PY - 2024 JO - Applied Sciences DO - 10.3390/app142411897 UR - https://doi.org/10.3390/app142411897 ER -
APA
Wawer, M., Chudziak, J. A., & Niewiadomska-Szynkiewicz, E. (2024). Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets. Applied Sciences. https://doi.org/10.3390/app142411897
Source records
- doaj · retrieved 2026-11-10T10:00:11.138Z