jackson-video-resources

jackson-video-resources / markov-hedge-fund-method

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Markov regime detection skill + one-shot install prompt + Pine indicator. Companion to Quant Series video 1. Framework by Roan (@RohOnChain).

19
12
85% credibility
Found May 20, 2026 at 40 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This project is a market analysis tool that helps everyday investors understand what 'regime' the market is in—Bull (rising), Bear (falling), or Sideways (stable). You simply name any stock or cryptocurrency, and it downloads the price history, analyzes how the market has been behaving, and tells you what regime we're in right now, how likely we are to stay there, and what might happen next. It also shows historical performance of this approach so you can see how it would have done in the past. The tool was created by Lewis Jackson based on a framework by Roan (@RohOnChain), and it works without needing any API keys or special accounts—just plug it in and ask about any asset.

How It Works

1
📺 You discover the method in a video

You watch a video about a hedge fund technique that predicts market conditions using mathematical patterns.

2
⚡ You install the analysis tool in seconds

With just two simple commands, the tool is ready to analyze any market you choose.

3
🔍 You ask about any asset

You simply ask 'What's the regime on BTC-USD?' or 'Analyze my SPY strategy' and the tool springs to life.

4
📊 The tool studies the price history

It downloads years of daily prices and labels each day as Bull, Bear, or Sideways based on how the market moved.

5
🔗 It maps how regimes connect

The tool builds a map showing how likely the market is to switch between conditions—like understanding the weather patterns.

6
You receive your personalized analysis
🎯
Current regime

You see if we're in a Bull, Bear, or Sideways market right now

🔮
Future probabilities

You see the odds of each regime continuing or changing tomorrow

📉
Historical performance

You see how this method would have performed over the past years

✅ You understand the market's heartbeat

You now know the current market condition, how sticky it might be, and what direction the signals suggest—so you can make more informed decisions.

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AI-Generated Review

What is markov-hedge-fund-method?

A Python tool that detects market regimes using a Markov framework. It labels each day as Bull, Bear, or Sideways based on rolling returns, then builds a transition matrix to forecast regime changes and calculate a directional signal. The tool includes a walk-forward backtest that reports Sharpe ratio and max drawdown without lookahead bias. You can feed it any ticker via yfinance or plug in your own CSV. It also ships a TradingView Pine Script indicator for live charting.

Why is it gaining traction?

The zero-dependency install and JSON output mode make it dead simple to slot into automated trading pipelines. The walk-forward backtest is incremental and O(n) instead of O(n^2), so it scales to decades of daily data without grinding to a halt. The optional Hidden Markov Model via hmmlearn adds a probabilistic upgrade path if you need it, with graceful degradation if the library is unavailable.

Who should use this?

Quant traders building systematic strategies who need a regime-aware filter. Algo developers who want to layer market state detection into an existing pipeline without rebuilding from scratch. Anyone running a trading agent who wants a structured JSON signal they can consume programmatically.

Verdict

This is a genuinely useful framework with a clean user interface, but with 19 stars and sparse documentation it is early-stage software. The credibility score of 0.85% reflects that low visibility and community uptake. Worth evaluating for the core algorithm if you understand Markov regime switching models, but treat the surrounding tooling as a beta. The Pine Script indicator and one-shot install experience are polished touches that suggest the author knows how to ship.

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