This repository provides a tool called pdf2code that converts quantitative finance research papers into prompts suitable for ChatGPT, which can then be used to generate corresponding code. The goal is to streamline the process of transforming complex financial models described in academic papers into functional scripts, enabling faster prototyping and experimentation in quantitative trading.

With this tool, you can extract the core ideas from research papers and efficiently turn them into actionable code using ChatGPT's powerful language model capabilities. This is particularly useful for researchers, developers, and quants looking to implement financial strategies described in academic literature without manually coding everything from scratch.

• Automated Conversion: Convert quantitative finance research papers into well-structured prompts.
• ChatGPT Integration: Directly use these prompts with ChatGPT to generate relevant Python code or other programming languages.
• Support for Various Models: Covers a range of quantitative models, including time series, statistical arbitrage, machine learning-based trading strategies, etc.
• Simplify Prototyping: Rapidly implement and test new trading strategies described in academic literature.
• GUI-Based PDF Selection: A graphical user interface allows users to easily select the PDF file for conversion.

To use this tool, you need to have Python installed. You can either clone this repository or directly download/copy the script into a .py file.

To clone the repository:

$ git clone https://github.com/lussifa/pdf2code.git
$ cd pdf2code

Alternatively, you can download or copy the pdf2code.py file and save it locally.

No additional dependencies are required for basic usage.

This is a single-file script that can be run directly. It is recommended to use it on Windows or Ubuntu with a GUI, as it will display a file dialog for selecting the PDF research paper.

To run the tool:

$ python pdf2code.py

A window will pop up allowing you to choose the PDF file containing the quantitative finance research paper. The tool will then process the file and generate a prompt for ChatGPT.

Suppose you have a research paper discussing a trading strategy based on moving averages. The tool will extract the core logic and generate a structured prompt, which you can feed to ChatGPT to create a Python implementation.

• Python 3.8+
• GUI support (e.g., Windows or Ubuntu with a graphical interface)

Contributions are welcome! If you find a bug or have an idea for a new feature, please open an issue or create a pull request.

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

• Inspired by the power of ChatGPT and the need for more efficient quantitative research implementation.
• Special thanks to the quant community for feedback and inspiration.

If you have any questions or need further assistance, feel free to leave me a message.