class: center, middle, inverse, title-slide .title[ # Stock Market Movement Prediction Using 8-K Filings ] .author[ ### Team Members: Abhishek Varma, Kevin Roy, Saurabh Shete ] .date[ ### December 11, 2024 ] --- ## Original Data Analytics Plan .large[ - **Objective**: Stock movement prediction using 8-K filings - **Dataset**: 22,490 rows, 5 columns - **Time Period**: 2010-2024 - **Companies**: Major corporations (PFIZER, MICROSOFT, APPLE, AMAZON, etc) ] --- ## Data Source and Structure .large[ **Dataset Details**: - **Source**: - SEC EDGAR database - Yahoo Finance - **Key Variables**: - CIK (Company Identifier) - Company Name - Filing Date - Event Information - Stock Movement Labels ] --- ## Top 10 Companies Analysis <!-- --> --- ## Data Preprocessing .large[ 1. **Text Processing**: - Tokenization & Normalization - Stop-word Removal - Special Character Cleaning 2. **Feature Engineering**: - Financial metrics extraction - Technical indicators - Text-based features ] --- ## Model Architecture .pull-left[ ### Deep Learning Model (H2O) - 3 hidden layers - Layer 1: 200 neurons - Layer 2: 100 neurons - Layer 3: 50 neurons - RectifierWithDropout activation ] .pull-right[ ### Training Features - Adaptive learning rate - Class balancing - Early stopping - L1/L2 regularization ] --- ## Model Performance * Overall Accuracy (74.27%) * LogLoss (0.6619) * Root Mean Squared Error (RMSE) (0.4585) --- ## Company-wise Performance <!-- --> --- ## Key Findings .large[ 1. **Overall Performance**: - 74.27% prediction accuracy - Consistent performance across companies - Strong financial sector predictions 2. **Technical Achievements**: - Successful text-market data integration - Effective deep learning implementation - Robust feature engineering ] --- ## Response to Peer comments - Comments related to performance evaluation were addressed. - Comments related to temporal pattern analysis were addressed. - Comments related to feature engineering were addressed. --- class: inverse, center, middle # Thank You! ## Questions?