Skip to content

jacobsterling/quantative-analysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

37 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Quantitative Analysis Notebooks

Welcome to the notebooks directory of our Quantitative Analysis and Strategy Creation project. This folder contains Jupyter notebooks that demonstrate various financial strategies, analyses, and backtesting results.

Directory Structure

notebooks/
├── back_testing/
│   ├── strategy_analysis_example.ipynb
│   └── CVDDivergence_analysis.ipynb
├── black_scholes/
│   └── hedging_strategies.ipynb
├── kucoin_futures_pairs_analysis.ipynb
├── order_heat_map.ipynb
├── portfolio_analysis.ipynb
└── trade_analysis.ipynb

Notebook Descriptions

Back Testing

The back_testing/ directory contains notebooks that utilize algorithms from the jacobsterling/trading-algorithms repository. These notebooks demonstrate the implementation and analysis of various trading strategies:

  • strategy_analysis_example.ipynb: A general example of strategy analysis using the backtesting framework.
  • CVDDivergence_analysis.ipynb: Analysis of the Cumulative Volume Delta (CVD) Divergence strategy.

Black-Scholes

  • hedging_strategies.ipynb: Explores option pricing and hedging strategies using the Black-Scholes model.

Other Analyses

  • kucoin_futures_pairs_analysis.ipynb: Analysis of futures trading pairs on the KuCoin exchange.
  • order_heat_map.ipynb: Visualization of order book data using heat maps.
  • portfolio_analysis.ipynb: In-depth analysis of portfolio performance and risk metrics.
  • trade_analysis.ipynb: Detailed examination of individual trades and their outcomes.

Usage

To use these notebooks:

  1. Ensure you have Jupyter Notebook or JupyterLab installed.
  2. Navigate to this directory in your terminal.
  3. Run jupyter notebook or jupyter lab to start the Jupyter server.
  4. Open the desired notebook to view, run, or modify the analyses.

Dependencies

These notebooks rely on various Python libraries for data analysis and visualization. Ensure you have installed all dependencies listed in the project's requirements.txt file.

Contributing

We welcome contributions to enhance these notebooks or add new analyses. Please refer to the main project README for contribution guidelines.

License

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

About

Quantative analysis notebooks, includes backtesting for developed algorithms

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors