Analysis: Price, patterns, and testing what you believe

This category covers the analytical toolkit that sits on top of price and volume data rather than financial statements. It begins with market structure on a chart — what a trend actually is, how to mark support and resistance so the levels mean something, and why timeframe selection changes the answer more than any indicator setting does. Candlestick and bar patterns are taught with their base rates rather than as folklore, so you know which formations carry information and which are noise dressed up as signal.

Indicators get treated as what they are: transformations of price that trade responsiveness against reliability. Moving averages and their crossovers, RSI and the difference between overbought and strong, MACD as a momentum derivative, Bollinger Bands as a volatility envelope, ATR for sizing and stop distance, and the volume family — on-balance volume, volume-weighted average price, accumulation and distribution. The recurring lesson is that indicators derived from the same input are not independent confirmation of each other, and that stacking five momentum oscillators tells you one thing five times.

The quantitative half of the library moves from single charts to populations of stocks. You will learn to build screens that express a thesis instead of just filtering on a number, to measure relative strength across sectors, and to think in terms of factors — value, momentum, quality, size, low volatility — and how they behave across regimes. Correlation and its instability during drawdowns get their own treatment, because diversification measured in calm markets tends to disappear exactly when it is needed.

Backtesting is where the category gets rigorous. Lessons cover look-ahead bias, survivorship bias in historical universes, transaction costs and slippage that turn profitable-on-paper systems into losers, in-sample versus out-of-sample splits, walk-forward validation, and the multiple-comparisons problem that makes a strategy tested a hundred ways look good by accident. You will learn to read equity curves for drawdown and recovery rather than for total return, and to judge a result by the number of independent trades behind it. The point of the category is not to find a pattern that worked; it is to be able to tell the difference between a pattern and a coincidence.