Min-max Scaling

What is Min-max Scaling?

Min-max scaling rescales a series to a fixed interval, usually 0 to 1 or 0 to 100, by subtracting the window minimum and dividing by the window range (maximum minus minimum). On charts it is almost always rolling: the extremes are taken over a trailing lookback, so each value states where the series sits inside its recent range. The Stochastic oscillator's %K is exactly this transform, min-max scaling the close against the highest high and lowest low of the lookback.

The appeal is comparability: once everything lives on the same bounded scale, oscillators with unlike units can share a panel, feed a composite score, or enter a model without one input dominating on magnitude alone. The cost is outlier sensitivity: a single extreme print stretches the range and compresses everything else toward the middle, which is why a Z-score or percentile rank is often preferred when the input has fat tails.

How traders use it

• To normalize unlike indicators onto one 0-100 panel or dashboard, so momentum, volume, and volatility readings can be compared, averaged, or scored side by side.
• As a position-in-range read on price itself: values near 1 mean the market is trading at the top of its N-bar range and values near 0 at the bottom, which is the raw material of stochastic-style logic.
• As feature scaling before model fitting, where bounded, comparable inputs keep distance-based and gradient-based methods from being dominated by whichever raw series has the largest units.