Stock Market Analysis
Overview
Time-series analysis and forecasting for major tech stocks (Apple, Microsoft, Amazon) using deep learning and traditional machine learning approaches.
Approach
Data:
- Historical stock data for top tech companies
- Feature engineering for time-series characteristics
Models:
- LSTM networks for sequence prediction
- Comparison with traditional ML regression models
- Qualitative analysis of prediction quality
Evaluation:
- Regression metrics (MAE, RMSE)
- Visual comparison of predicted vs actual prices
- Analysis of model behavior during volatile periods
Key Learnings
- Time-series forecasting requires careful feature engineering
- LSTM networks capture temporal dependencies effectively
- Financial data presents unique challenges (non-stationarity, regime changes)
Tech Stack
Python TensorFlow/Keras LSTM Pandas NumPy Matplotlib