Scholarlink

In the realm of finance, where news sentiment can sway markets, our study explores the synergy between FinBERT, a specialized BERT variant trained for finance, and Ridge Regression, an interpretable machine learning model. As financial decisions hinge on both performance and transparency, we prioritize models that strike a balance, avoiding excessive complexity while delivering robust predictions. Leveraging Google News as our source, we harness its clustering capabilities to consolidate relevant articles. Through this fusion of FinBERT’s sentiment analysis and Ridge Regression, we offer actionable insights into stock market behavior while demystifying the decision-making process. Our research emphasizes the importance of maintaining transparency in financial predictions.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Interpretable Machine Learning and Sentiment Analysis for Enhanced Predictive Accuracy in Financial Markets

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Saideva Sathvik Ravula,
  • S. V. S. N. Sarma,
  • Gudipudi Radhesyam

摘要

In the realm of finance, where news sentiment can sway markets, our study explores the synergy between FinBERT, a specialized BERT variant trained for finance, and Ridge Regression, an interpretable machine learning model. As financial decisions hinge on both performance and transparency, we prioritize models that strike a balance, avoiding excessive complexity while delivering robust predictions. Leveraging Google News as our source, we harness its clustering capabilities to consolidate relevant articles. Through this fusion of FinBERT’s sentiment analysis and Ridge Regression, we offer actionable insights into stock market behavior while demystifying the decision-making process. Our research emphasizes the importance of maintaining transparency in financial predictions.