mean-reversion-engine

Identify mean-reversion opportunities in price data using Bollinger, RSI, and Z-score methods.

10|2|Updated Mar 8, 2026

Search Tags:#strategy #finance #trading #rsi #mean-reversion #bollinger #zscore

Ready to run

npx skills add https://github.com/mahmoud20138/Tradecraft --skill mean-reversion-engine

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mean-reversion-engine
Source: https://github.com/mahmoud20138/Tradecraft/tree/main/plugins/tradecraft/skills/mean-reversion-engine
Command: npx skills add https://github.com/mahmoud20138/Tradecraft --skill mean-reversion-engine

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides ready-to-use mean-reversion templates to identify and act on reversion opportunities in price data, helping traders exploit range-bound moves with structured signals.

Core Features & Use Cases

Bollinger bounce detection for range-bound assets.
RSI extreme fade with divergence checks to confirm reversals.
Z-score reversion signals with mean and distance-to-mean metrics.
Batch analysis via scan_all to generate a consolidated signal map for a given symbol.

Quick Start

Call MeanReversionEngine.scan_all on a price DataFrame named df to obtain signals.

Frequently Asked Questions about mean-reversion-engine

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify mean-reversion opportunities in ranging markets using Python?▼

To identify mean-reversion opportunities in ranging markets, you can apply Bollinger, RSI, and Z-score methods to price history DataFrames using pandas and numpy to generate structured trading signals.

What is the best way to detect Bollinger bounce signals for range-bound assets?▼

The best way to detect Bollinger bounce signals for range-bound assets is to run batch analysis on price data, which returns a consolidated signal map with target and risk metrics for the given symbol.

Can I use RSI extreme fade with divergence checks to confirm price reversals?▼

Yes, you can use RSI extreme fade with divergence checks to confirm price reversals, generating structured signal dictionaries that indicate when a ranging market asset is likely to revert to its mean.

How do I calculate Z-score reversion signals with distance-to-mean metrics?▼

You calculate Z-score reversion signals by analyzing price histories with numpy and pandas, which outputs structured dictionaries containing the signal, mean, and distance-to-mean metrics for the asset.

Does mean-reversion trading work with trending markets or only ranging regimes?▼

Mean-reversion trading is designed for ranging regimes and may underperform in trending markets. These templates exploit range-bound moves, so you should avoid applying them when price data shows a clear directional trend.

Do I need pandas and numpy to generate mean-reversion signals from price data?▼

Yes, you need pandas and numpy to generate mean-reversion signals, as the static methods processing price histories depend on these libraries to return structured dictionaries with signal and risk metrics.