Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models

By Kelvin J.L. Koa, Yunshan Ma, Ritchie Ng, Tat-Seng Chua

Published 2024-02-29

Everscope rating

1360.8

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

4 / 5

About this paper

Methodology: Summarize-Explain-Predict (SEP) framework. Problem types: Classification, Natural Language Processing, Time Series Forecasting, Portfolio Optimization.

arXiv:2402.03659 · Code · Paper rankings

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