https://github.com/ruoheng-du/deep-learning-stock-return
The Pitfall and Opportunity of Deep Learning in Stock Return Prediction | Fall 2023
https://github.com/ruoheng-du/deep-learning-stock-return
deep-learning lstm stock-return-predictions transformers
Last synced: 3 months ago
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The Pitfall and Opportunity of Deep Learning in Stock Return Prediction | Fall 2023
- Host: GitHub
- URL: https://github.com/ruoheng-du/deep-learning-stock-return
- Owner: ruoheng-du
- Created: 2024-08-22T14:58:10.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-30T20:11:15.000Z (9 months ago)
- Last Synced: 2025-01-15T19:28:33.397Z (4 months ago)
- Topics: deep-learning, lstm, stock-return-predictions, transformers
- Language: Jupyter Notebook
- Homepage:
- Size: 4.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# The Pitfall and Opportunity of Deep Learning in Stock Return Prediction | Fall 2023
This is the repository for my capstone project during Fall 2023. The project investigates the effectiveness and challenges of using deep learning techniques for predicting stock returns. It aims to identify the strengths and limitations of deep learning models in financial forecasting. The capstone project involves: 1) establishing performance benchmarks using autoregressive and multilinear models; 2) testing advanced deep learning models such as LSTM networks and Transformers; 3) evaluating how market volatility affects prediction accuracy by applying filtering and smoothing techniques. For detailed process and insights, please refer to the report uploaded here: [NYUSH_DS_Capstone_Report_Ruoheng](./NYUSH_DS_Capstone_Report_Ruoheng.pdf). Feel free to email me at [email protected] for any more information.
