Developing a Model to Make More Informed Decisions Related to Anomaly Detection

The team adopted a Three-Pronged approach for Data Preparation - Explicit Rules, K-Means Clustering and Random Forest, and combined the outputs to identify the common stocks flagged for anomalies across the selected period by all 3 models. They also developed a Tableau dashboard to provide a comprehensive analysis of each stock’s performance in terms of both selected market indicators and financial ratios.