GlossaryAdvanced
Fisher Transform
A mathematical transformation that reshapes price data to more closely resemble a normal distribution, making turning points sharper and clearer.
The Fisher Transform, developed by John Ehlers, applies a mathematical transformation to normalized price data, reshaping its distribution to more closely resemble a Gaussian (normal, bell-curve) distribution.
Because raw price data doesn't naturally follow this distribution, the transform is intended to make extreme turning points stand out more sharply and clearly than they would in an unmodified price oscillator. See Kaavon's dedicated Fisher Transform article for the full calculation.
Examples
- The Fisher Transform's extreme readings are intended to stand out more sharply than an equivalent extreme in an untransformed price oscillator.
- A sharp turn in the Fisher Transform line is commonly watched as a potential signal of an imminent price reversal.