hurst-pullback

Reproducible Python implementation of the Hurst-Regime Pullback Strategy for index futures (ES, NQ, EMD, YM) — QuantConnect-ready research framework.

Development

Quick setup using UV, make sure you have installed it before doing any of the following steps:

uv sync

This creates .venv, installs required packages and ensures the correct Python version.

.\.venv\Scripts\Activate.ps1

.\.venv\Scripts\activate.bat

source .venv/bin/activate

Python dependencies and tools are managed with UV. This is how to install a library (UV will add this to the dependencies list automatically).

uv add pandas  # code dependencies
uv add --dev black # development tools

All flags and input parameters are initialized in the file base.yaml. You need to import the file, this is an example:

import yaml

yaml_path = Path().resolve().parent / "configs" / "base.yaml"
with open(yaml_path, "r") as f:
    config = yaml.safe_load(f)

Then you can use initialized variables using this syntax:

config["data"]["clean_NQ"]  # this line select the path of "clean_NQ" which is part of the subset data in the base file