Data‑Driven Exploration of Key Factors in Stock Market Success

• Gathered financial data from 7,000+ listed companies and key macroeconomic indicators using web scraping. • Doubled data quality by using K‑Means for outlier detection and applying accounting principles for data cleanup and reconstruction. • Analyzed a 40‑year range of financial data, considering over 100 factors including macroeconomic signals and financial records. • Developed an XGBoost regression model with the aim of predicting future stock prices using historical financial fundamentals, while elucidating the significance of these fundamentals to stock performance.