Prophet Model for Financial Predictions

This repository contains an implementation of an Prophet model, specifically designed for predicting the prices of financial instruments such as currencies, stocks, and cryptocurrencies. The Prophet algorithm leverages gradient boosting techniques, enabling it to capture intricate patterns in price movements and handle various dataset characteristics effectively. This approach enhances the accuracy and robustness of price forecasts across various datasets.

This is the original code sample for the Prophet model. Explore my GitHub repository for additional models and implementations that cater to different financial prediction needs.

Performance Metrics

BTC-USD (Bitcoin)

Metric	Open	High	Low	Close
Mean Squared Error	0.001128	0.001091	0.001124	0.001130
Mean Absolute Error	0.0252	0.0242	0.0256	0.0252
R-squared	0.9581	0.9599	0.9567	0.9583
Median Absolute Error	0.0192	0.0185	0.0206	0.0197
Explained Variance Score	0.9590	0.9607	0.9577	0.9591

GC=F (Gold Futures)

Metric	Open	High	Low	Close
Mean Squared Error	0.002564	0.002654	0.002299	0.002728
Mean Absolute Error	0.0370	0.0371	0.0369	0.0373
R-squared	0.6793	0.6716	0.7152	0.6592
Median Absolute Error	0.0264	0.0269	0.0278	0.0271
Explained Variance Score	0.6801	0.6725	0.7154	0.6596

EURUSD (Euro/US Dollar)

Metric	Open	High	Low	Close
Mean Squared Error	0.003896	0.006249	0.004571	0.003901
Mean Absolute Error	0.0460	0.0481	0.0465	0.0461
R-squared	0.9246	0.8811	0.9118	0.9245
Median Absolute Error	0.0361	0.0354	0.0370	0.0358
Explained Variance Score	0.9249	0.8813	0.9123	0.9248

GSPC (S&P 500 Index)

Metric	Open	High	Low	Close
Mean Squared Error	0.002229	0.002056	0.002433	0.002483
Mean Absolute Error	0.0370	0.0352	0.0380	0.0382
R-squared	0.8571	0.8728	0.8455	0.8481
Median Absolute Error	0.0308	0.0284	0.0321	0.0308
Explained Variance Score	0.8585	0.8745	0.8472	0.8499

GSPC (S&P 500 Index)

Metric	Open	High	Low	Close
Mean Squared Error	0.0002814720	0.0002205432	0.0002693110	0.0003159326
Mean Absolute Error	0.0120022037	0.0102594281	0.0116081449	0.0128960376
R-squared	0.9793603517	0.9845881815	0.9800899726	0.9777500754
Median Absolute Error	0.0087334798	0.0070796587	0.0083986821	0.0093586147
Explained Variance Score	0.9793616049	0.9847025079	0.9801110322	0.9777512454

Related Websites

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Magical Prediction

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About This Project

This Prophet model is an initial implementation, released for public use. The project demonstrates the potential of deep learning models for financial predictions. While this repository focuses on Prophet, I have also utilized other models, the code for which is available on my GitHub[https://github.com/taleblou/].

How to Use

1. Clone this repository.
2. Install the required libraries: pip install -r requirements.txt
3. Prepare your dataset and follow the instructions in the notebook or script.
4. Run the model and evaluate its performance using the provided metrics.

License

This project is open-source and available for public use under the MIT License. Contributions and feedback are welcome!