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Miha Kralj 92709ef2ed Add Stochastic Oscillator implementation and validation tests

- Implemented Stochastic Oscillator (%K and %D) in Stoch.cs with streaming and batch processing capabilities.
- Added validation tests for the Stochastic Oscillator in Stoch.Validation.Tests.cs, ensuring consistency with Skender.Stock.Indicators.
- Created documentation for the Stochastic Oscillator in Stoch.md, detailing its mathematical formula, architecture, parameters, and common pitfalls.
- Updated project file to include necessary numeric libraries for highest and lowest calculations.

2026-02-12 14:29:54 -08:00

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Fisher Transform (FISHER)

Overview

The Fisher Transform converts price data into a Gaussian normal distribution using the inverse hyperbolic tangent function (arctanh), producing sharp turning points that aid in identifying potential price reversals. Developed by John Ehlers in 2002.

Formula

displacement = floor(period / 2) + 1
normalized = 2 × (price − lowest) / (highest − lowest) − 1
value = α × normalized + (1 − α) × value[1]
value = clamp(value, −0.999, 0.999)
Fisher = 0.5 × ln((1 + value) / (1 − value))
Signal = α × Fisher + (1 − α) × Signal[1]

Where:

highest / lowest = highest high / lowest low over period bars
α = EMA smoothing factor (default: 0.33)
The transform applies arctanh to the smoothed, normalized price

Parameters

Parameter	Type	Default	Range	Description
period	int	10	1–500	Lookback for min/max normalization
alpha	double	0.33	(0, 1]	EMA smoothing factor

Outputs

Output	Description
Fisher	Primary Fisher Transform line
Signal	EMA-smoothed signal line

Interpretation

Extreme Values: Fisher > +2 suggests overbought; Fisher < −2 suggests oversold
Crossovers: Fisher crossing above Signal = bullish; below = bearish
Zero-Line: Crossing zero indicates trend direction change
Divergence: Price vs. Fisher divergence warns of potential reversal
Sharp Turns: Fisher produces sharper peaks/troughs than raw oscillators

Limitations

Not bounded — extreme values depend on price volatility
Can produce whipsaw signals in choppy/ranging markets
Lagging due to EMA smoothing
Normalization range affected by lookback period choice
Domain protection (clamping to ±0.999) can compress extreme values

References

Ehlers, John F. "Using The Fisher Transform." Stocks & Commodities, 2002.
PineScript source: fisher.pine

Source

Fisher.cs | Tests | Validation

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