Project information
- Category: Time Series
- Project date: 20 Dec, 2023
- Project URL: Project Link
Project Description
- Collaborated on an academic group project focused on predicting stock price movements at market close, utilizing provided data for time series analysis
- Employed and fine-tuned three LSTM models tailored for the specific task of forecasting stock price movement within the given time frame.
- Conducted rigorous evaluation and comparison of the LSTM models, selecting the best-performing model for the final predictions.
- Achieved a notable rank of 774 out of 4436 participants on the Kaggle leaderboard, showcasing the model's competitive performance in real-world scenarios.