Fisher and Inverse Fisher Transforms for Oscillator Trading Signals

Summary

The article introduces the Fisher Transform as a way to reshape normalized market-cycle values whose distribution may concentrate near cycle extremes rather than follow a Gaussian pattern. It describes normalizing prices over a rolling range before applying the transform, which amplifies extreme movements, and presents an MQL5 indicator using median prices and a delayed signal line. It then explains the inverse transform, which compresses large inputs toward positive or negative one, and applies it to an oscillator to create sharper signals.

An Expert Advisor using the indicator is backtested, but the author says it was not profitable across all assets and timeframes and reports tuning it for EURUSD on the one-hour timeframe. The material motivates the transforms with a cited analysis of U.S. Treasury bond prices and illustrates implementation, but does not establish robust out-of-sample performance. Results depend on the normalization, oscillator, settings, asset, and timeframe, so the example should be treated as exploratory rather than general evidence of profitability.

Key ideas

• The Fisher Transform is applied to normalized prices to emphasize values near the ends of a market cycle.
• The inverse transform can compress oscillator outputs toward positive or negative one, creating more decisive signals.
• The MQL5 example normalizes median prices over a rolling range and includes a one-bar delayed signal line.
• The example Expert Advisor was not profitable across every asset and timeframe and was tuned for one EURUSD setting.
• The article presents an implementation and motivating distribution argument, not proof of robust trading performance.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.