Is a powerful engine for finding, analyzing and predicting. It uses a dual-metric quantitative similarity engine to scan historical price data. For each analysis, it extracts the most recent price pattern (your chosen window, e.g. 3 months) and normalises it, then slides that template across decades of historical candles, scoring every possible position using two equally-weighted measures: Pearson correlation (which captures the overall shape similarity between two normalised price curves) and directional agreement (which counts what percentage of individual up/down moves match between the two segments). The two scores are averaged into a single 0–100% similarity score, the top non-overlapping matches are ranked, and the proportion that led to a bullish or bearish outcome over your chosen forward window becomes the probability estimate. The more matches found, and the higher their average similarity, the more statistically meaningful the signal — which is what the Signal Quality rating reflects.

"History repeats itself" and "Those who know the past can predict the future" are well-known phrases. The idea is simple — understanding historical patterns and events can offer meaningful insights into what may come next. Historical cycles tend to recur. Most people fail to recognise them, but the knowledgeable and experienced can read the signs and anticipate probable outcomes. The same or similar patterns will, more often than not, produce the same results — and financial markets are no exception. Markets are driven by social, political, economic, and environmental forces. Yet within that noise, pattern signatures exist — codes waiting to be deciphered, pointing toward future direction. Pattern analysis is a well-established method with an extensive body of literature behind it. Consider candlestick theory in financial markets: a widely accepted and practiced approach that is, at its core, a pattern recognition method. If we accept this premise, then a pattern — repeatedly confirmed across history — can be a powerful edge in predicting the probable direction of future market movement, that's why we have created  PATTERNicus.