Distilled ChatGPT Topic & Sentiment Modeling with Applications in Finance
<|reference_start|>Distilled ChatGPT Topic & Sentiment Modeling with Applications in Finance: In this study, ChatGPT is utilized to create streamlined models that generate easily interpretable features. These features are then used to evaluate financial outcomes from earnings calls. We detail a training approach that merges knowledge distillation and transfer learning, resulting in lightweight topic and sentiment classification models without significant loss in accuracy. These models are assessed through a dataset annotated by experts. The paper also delves into two practical case studies, highlighting how the generated features can be effectively utilized in quantitative investing scenarios.<|reference_end|>
@article{gandouet2024distilled,
    title={Distilled ChatGPT Topic & Sentiment Modeling with Applications in
  Finance},
    author={Olivier Gandouet, Mouloud Belbahri, Armelle Jezequel, Yuriy Bodjov},
    journal={arXiv preprint arXiv:2403.02185},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.02185},
    primaryClass={cs.LG cs.CE cs.CL}
}