Moving Average Convergence: 10 Crossover & Ribbon Strategies

by PyQuantLab

Overview

Navigate the complexities of price charts and find clarity amidst market noise. This mini-ebook introduces the fundamental tool of Moving Averages (MAs), your guide to smoothing volatility and understanding the bigger picture. Learn how MAs average prices over time to filter out random fluctuations and reveal underlying trends and momentum.

Discover why understanding MAs is essential for any trader. Explore their versatility in trend identification, support/resistance, signal generation, and momentum gauging. Master the core concepts that form the foundation for advanced indicators like MACD and Bollinger Bands. This guide covers key MA types including SMA, EMA, DEMA, TEMA, and the Guppy Multiple Moving Average (GMMA). Practical Python examples using Backtrader illustrate the strategies in action.

What You'll Learn: 10 MA Strategies

• Strategy 1: The Foundation - Simple EMA Crossover (e.g., 9 EMA vs. 21 EMA)
• Strategy 2: The Long View - Golden Cross & Death Cross (50 SMA vs. 200 SMA) as Filters
• Strategy 3: Adding Confirmation - Triple EMA Crossover (e.g., 5, 10, 20 EMA)
• Strategy 4: Riding the Wave - MA Ribbon Expansion & Contraction Signals
• Strategy 5: Decoding Sentiment - Guppy MMA for Trend Filtering & Entry Timing
• Strategy 6: The Pullback Play - Price Bouncing Off a Key MA (e.g., 20 EMA or 50 SMA)
• Strategy 7: Early Warnings - Trading MA Slope Changes
• Strategy 8: Reducing Lag - Using DEMA/TEMA Crossovers (with caution)
• Strategy 9: Trend Is Your Friend - Combining Moving Averages
• Strategy 10: The Rubber Band Effect - Basic MA Price Distance for Reversion Clues

Who Is This Book For?

• Python Developers exploring algorithmic trading and quantitative finance.
• Manual Traders aiming to automate, backtest, and refine moving average-based strategies.
• Finance Students & Hobbyists seeking a practical, hands-on guide to MA trading techniques.
• Anyone looking for a structured approach to applying various Moving Average strategies effectively.