https://github.com/gregoritsch3/ml_eda_classification_goldpriceprediction
An EDA and Machine Learning Classification project on the IAU Gold ETF demonstrating the use of yfinance, stockstats, Time Series Split, Feature Expansion (SMA, EMA, lagged features, RSI-14, CL=F Close Price, etc.), Model Evaluation and Hyperparameter Tuning. The model predicts Gold price movement (1-up, 0-down) on a weekly basis and performs well.
https://github.com/gregoritsch3/ml_eda_classification_goldpriceprediction
price-prediction quantitative-finance randomforestclassifier scikit-learn yfinance
Last synced: 8 months ago
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An EDA and Machine Learning Classification project on the IAU Gold ETF demonstrating the use of yfinance, stockstats, Time Series Split, Feature Expansion (SMA, EMA, lagged features, RSI-14, CL=F Close Price, etc.), Model Evaluation and Hyperparameter Tuning. The model predicts Gold price movement (1-up, 0-down) on a weekly basis and performs well.
- Host: GitHub
- URL: https://github.com/gregoritsch3/ml_eda_classification_goldpriceprediction
- Owner: Gregoritsch3
- Created: 2024-12-26T09:03:33.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-12-30T12:04:12.000Z (9 months ago)
- Last Synced: 2025-02-20T07:14:13.216Z (8 months ago)
- Topics: price-prediction, quantitative-finance, randomforestclassifier, scikit-learn, yfinance
- Language: Jupyter Notebook
- Homepage: https://finance.yahoo.com/quote/IAU/
- Size: 1.17 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# ML_EDA_Classification_Gold
An EDA and Machine Learning Classification project on the IAU Gold ETF demonstrating the use of yfinance, stockstats, Time Series Split, Feature Expansion (SMA, EMA, lagged features, RSI-14, CL=F Close Price, etc.), Model Evaluation and Hyperparameter Tuning. The model predicts Gold price movement (1-up, 0-down) on a weekly basis using a RandomForestClassifier and performs well. With minimal effort, the model is to be expanded so as to predict the actual Close Price as well.