SARF: Enhancing Stock Market Prediction with Sentiment-Augmented Random Forest

Understand

Stock trend forecasting, a challenging problem in the financial domain, involves ex-tensive data and related indicators.

• Relying solely on empirical analysis often yields unsustainable and ineffective results.
• Machine learning researchers have demonstrated that the application of random forest algorithm can enhance predictions in this context, playing a crucial auxiliary role in forecasting stock trends.
• This study introduces a new approach to stock market prediction by integrating sentiment analysis using FinGPT generative AI model with the traditional Random Forest model.