Skip to main content

Quantitative Pattern Finder

In short

Quantitative pattern recognition across price, volume, and fundamental data

A quantitative analysis framework that searches for statistical patterns in a stock's historical data. It looks for recurring seasonal trends, price anomalies, correlation shifts, and mean-reversion setups that may signal upcoming moves.

Use this framework when you want a data-driven, systematic analysis of a stock's behaviour. It goes beyond traditional technical analysis to find statistical edges in price patterns, earnings seasonality, sector rotation signals, and cross-asset correlations.

Related concepts

  • Simple Moving Average (SMA) — Take the last 50 days of prices and average them. That's the 50-day SMA. It smooths out daily noise so you can see the real trend. Price above its SMA = uptrend; below = downtrend.
  • Bollinger Bands — Three lines around a stock's price: a middle average and two outer bands. When the price touches the upper band, it might be overbought. Touch the lower band, possibly oversold. When the bands squeeze together, a big move is coming.
  • Volume Profile — Volume profile shows where most trading happened at different price levels. Heavy trading at a price means traders consider it fair value. Low trading zones are areas where price moves fast.