https://github.com/kostadinlambov/algorithmic-trading-bot
The project aims to evaluate the predictive performance of different machine learning (ML) algorithms for Bitcoin trading. The proposed trading strategy integrates key technical indicators, including the Relative Strength Index (RSI), Simple and Exponential Moving Averages, and the Moving Average Convergence Divergence (MACD).
https://github.com/kostadinlambov/algorithmic-trading-bot
lightgbm machine-learning matplotlib mlflow numpy optuna pandas pickle random-forest scikit-learn scipy seaborn statsmodels xgboost
Last synced: 3 months ago
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The project aims to evaluate the predictive performance of different machine learning (ML) algorithms for Bitcoin trading. The proposed trading strategy integrates key technical indicators, including the Relative Strength Index (RSI), Simple and Exponential Moving Averages, and the Moving Average Convergence Divergence (MACD).
- Host: GitHub
- URL: https://github.com/kostadinlambov/algorithmic-trading-bot
- Owner: kostadinlambov
- Created: 2024-11-10T13:26:08.000Z (11 months ago)
- Default Branch: master
- Last Pushed: 2024-12-10T22:47:27.000Z (10 months ago)
- Last Synced: 2025-06-10T04:05:58.428Z (4 months ago)
- Topics: lightgbm, machine-learning, matplotlib, mlflow, numpy, optuna, pandas, pickle, random-forest, scikit-learn, scipy, seaborn, statsmodels, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 126 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md