Automated Stock and Crypto Trading Strategies

Transition from emotional decision-making to disciplined, systematic investing with quantitative strategies. This written course provides a structured introduction to designing, testing, and managing automated trading models for both stock and cryptocurrency markets. You will gain a clear understanding of factor-based investing, risk metrics, and strategy formulation to build consistent rule-based workflows. What you'll learn: - Understand fundamental quantitative trading terms, market mechanics, and strategy architecture - Design rule-based entry and exit conditions using value, momentum, and technical indicators - Apply backtesting principles to evaluate historical performance while avoiding overfitting - Implement position sizing, stop-loss rules, and drawdown control for robust risk management - Analyze performance metrics including Sharpe ratio, maximum drawdown, and win rate - Explore modern execution concepts, slippage modeling, and multi-asset portfolio balancing The text begins with foundational market concepts and terminology before progressing step-by-step through strategy development, backtesting methodology, and portfolio protection. Designed for beginners and intermediate traders alike, no prior programming experience is required to understand and apply these concepts. Start reading today to establish a disciplined, data-driven approach to the markets.