Web-Mined Hypothesis Generation for Financial Markets: An Autonomous Backtesting Framework
Abstract
Financial markets are increasingly influenced by vast amounts of unstructured web data such as regulatory filings and social media, making it challenging to extract actionable insights. Traditional approaches to hypothesis generation rely heavily on expert knowledge and are often slow, subjective, and inefficient. There is a pressing need for automated systems that can mine financial data at scale, generate hypotheses, and validate them in real-time.
Fields of Study & Subjects
Stock Market Forecasting Methods
Financial Markets and Investment Strategies
Web Data Mining and Analysis
Publication details
- Journal / source
- ACM International Conference on Web Search and Data Mining (WSDM)
- Pages
- 1384–1385
- Publication date
- 16 February 2026
- Language
- EN