technical-analysis-educator

Technical analysis education requires structured explanations of indicator calculations, interpretations, and real-world applications. This Skill provides didactic templates for teaching RSI, MACD, and moving averages with clear step-by-step breakdowns, overbought/oversold concepts, and common trading mistakes, plus reproducible Python examples using yfinance and pandas-ta.

Yes. This Skill includes Malaysian market context and structured teaching patterns for designing backtesting exercises. It integrates yfinance for data retrieval, pandas-ta for indicator calculation, and plotly or mplfinance for visualization, enabling you to build complete educational modules with real market data.

Chart patterns and volume analysis require visual clarity and practical interpretation. This Skill provides teaching templates that explain pattern recognition, volume signals, and their relationship to price action, supported by code examples using mplfinance and plotly for clear visual demonstrations.

Structure lessons by explaining SMA versus EMA calculation methods, common period settings, and signal generation rules. This Skill supplies didactic patterns for introducing these concepts with Malaysian stock examples, code walkthroughs using pandas-ta, and practice exercises to reinforce identification of crossover signals.

While not strictly required, Python libraries like yfinance, pandas-ta, plotly, and mplfinance enable reproducible, validated examples that students can run independently. This Skill integrates these tools to support hands-on learning, data validation, and professional-grade visualizations within educational content.

Risk management education covers position sizing, stop-loss placement, and portfolio diversification principles. This Skill provides teaching resources and structured patterns for explaining these concepts alongside technical indicators, helping students understand how risk controls complement technical analysis strategies.