humbldata 1.23.0

open-sourcing the math behind major financial institutional investors/banks. this package connects financial data analysis to the humblFINANCE website.

humblDATA

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humbldata connects the humblfinance web app to its data sources and in-house analysis. A thin wrapper around the most popular open-source financial data providers, with some extra flair to use the same tools and math as the big guys. how do i know? because i used to pay a pretty penny for it! no longer... OSS is here to save the day!

🌟 Main Features 🌟

• humblCHANNEL

  • Quantitative trading signal tool that provides objective, mathematics-based buy and sell signals
  • Works with any tradable asset with available time series data
  • Customizable for different trading styles (day trading, swing trading, long-term investing)
  • Eliminates emotional decision-making with precise price channels

• humblCOMPASS

  • Economic regime identification and asset allocation guidance
  • Helps navigate different market conditions with data-driven insights
  • Provides strategic investment direction aligned with current market regimes

• humblMOMENTUM

  • Momentum-based signal indicators for timing market entries and exits
  • Track asset performance relative to market trends
  • Identify emerging opportunities before they become mainstream

• humblPORTFOLIO

  • Interactive portfolio management dashboard
  • Integrates data from humblCHANNEL and humblCOMPASS
  • Provides real-time asset overview with buy/sell recommendations
  • Risk management tools to prevent significant drawdowns

• Realized Volatility Estimators

  • All volatility calculations from Euan Sinclair's book, plus additional models
  • ⚡ Lightning fast estimators powered by Rust under the hood
  • Essential for accurate risk assessment and position sizing

Getting Started

Install with pip:

pip install humbldata

Install with poetry:

poetry add humbldata

Install with uv:

uv add humbldata

Documentation

For complete documentation on the library's features, architecture, and how to contribute, please visit: https://humblfinance.github.io/humblDATA/