This repository contains the code and analysis for my data analytics project in a Kaggle hackathon, where the goal was to predict stock prices and develop a strategy (Hold, Buy, or Sell) based on historical data.
I achieved the 32nd position out of 274 participants on the Kaggle leaderboard for this hackathon.
Model Used: Linear Regression
Additional Note: Experimentation with ARIMA was conducted initially, but linear regression outperformed it.
Ensemble Learning Techniques:
Base Model: XGBoost
Final Prediction: Soft Voting among ensemble models.
Clone this repository to your local machine.
Open the Kaggle notebook for step-by-step analysis.
Review the code and comments for a detailed understanding of the data preprocessing and modeling process.
Execute the notebooks to generate predictions for the 'Close' and 'Strategy' columns.
- Urvashi Bhargava