Correlation Analysis of XAUUSD, BTCUSD, and Forex Pairs

This project explores the correlations between XAUUSD (Gold), BTCUSD (Bitcoin), and major forex pairs, including;

• EURUSD
• USDCAD
• GBPUSD
• AUDUSD and
• DXY (Dollar Index). The analysis leverages Python and the Yahoo Finance API to provide insights into how these instruments relate to one another.

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📈 Key Features

• Comprehensive Analysis: Examines historical daily data for XAUUSD, BTCUSD, and major forex pairs.
• Statistical Insights: Computes correlation matrices and rolling correlations.
• Visualizations: Heatmaps and line charts to interpret relationships.
• Automated Data Retrieval: Utilizes Yahoo Finance API for reliable and up-to-date financial data.

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🛠️ Requirements

Ensure you have the following Python libraries installed:

pandas
matplotlib
seaborn
yfinance

🚀 Installation

Clone the repository:

https://github.com/amoakoh22/Forex-Pairs-Correlation-Analysis.git

Navigate into the project directory:

cd Forex-Pairs-Correlation-Analysis

Install the required libraries:

pip install -r requirements.txt

requirements.txt

💻 Usage

• Open the notebooks/xauusd_vs_forex_pairs_correlation_analysis.ipynb file in Jupyter Notebook or Google Colab.
• Run all cells to:
  • Fetch historical data
  • Compute correlations
  • Generate visualizations
• Explore the results , which includes:
  • Heatmaps
  • Rolling correlation plots

📊 Results

• Correlation Matrix Heatmap: This heatmap displays the statistical relationships between XAUUSD, BTCUSD, and major forex pairs over the selected timeframe.

• Rolling Correlation Plots: 30-day rolling correlations help analyze dynamic relationships, offering deeper insights into changing trends.

🤝 Contribution

Contributions are welcome! --To contribute:

• Fork the repository.
• Create a feature branch:

git checkout -b feature-name

Commit your changes and push:

git commit -m "Description of feature"

• Push your changes

git push origin feature-name

• Create a pull request.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

🖋️ Author

This project was developed by Samuel Amoakoh, a certified data scientist and mathematician with expertise and interests in:

• Financial Analytics
• Data Science
• Artificial Intelligence/Machine Learning (AI/ML)
• Sustainable Waste Management
• Policy Analysis

Samuel is passionate about leveraging data-driven insights to solve real-world challenges across diverse fields.

🔗 Connect

For more insights, follow or connect with me on:

• LinkedIn
• GitHub