The study ‘Distilled ChatGPT Topic & Sentiment Modeling with Applications in Finance’ details the use of ChatGPT in creating models for topic and sentiment analysis, which are then applied to financial contexts such as earnings calls analysis. The paper showcases knowledge distillation and transfer learning techniques to develop compact models. * Utilizes ChatGPT for generating interpretable features in financial analysis. * Combines knowledge distillation with transfer learning for model training. * Lightweight models maintain accuracy while being evaluated through expert-annotated datasets. * Features are used in case studies that reveal practicality in quantitative investing scenarios. This utilization of ChatGPT holds promise for enhancing feature generation in financial analysis, which could revolutionize quantitative strategies and investment decision-making processes.