MT4: go here
MT5: go here
Background & CareerEhlers trained as an electrical engineer: he holds a BSEE and MSEE from the University of Missouri. Later, he completed doctoral work at George Washington University, specializing in fields & waves and information theory.
Before becoming a full-time independent trader, he worked at Raytheon, retiring as a Senior Engineering Fellow.
He began trading privately in 1976. Over time, his engineering background shaped his approach to market analysis and algorithmic trading.
What He’s Known For — DSP + Market AnalysisEhlers is widely regarded as a pioneer in applying digital signal processing (DSP) — including spectral analysis and filter theory — to financial market data (stocks, futures, forex, etc.).
One of his landmark innovations: the MESA algorithm (Maximum Entropy Spectrum Analysis), a method to detect dominant cycles in price data and adapt indicator parameters accordingly, rather than relying on arbitrary/fixed periods.
His philosophy: before coding or deploying any trading technique, one should test it on theoretical waveforms (idealized data) to validate the math; only then apply to real-world data. In his view, this reduces overfitting and miscalibration.
Publications & Code — For Traders & CodersEhlers has authored numerous books, such as MESA and Trading Market Cycles, Rocket Science for Traders, and Cybernetic Analysis for Stocks and Futures.
He has been a frequent contributor to Technical Analysis of Stocks & Commodities magazine (often abbreviated “S&C Magazine”), where he published many indicator designs, trading system ideas, and code snippets (e.g. for various trading platforms).
His indicators often aim for “zero-lag” or minimal-lag filtering — smoothing price data without introducing too much delay. Tools like the “Directional Movement w/ Hann Windowing (DMH)”, “Zero-Lag filters”, “Laguerre filters”, custom oscillators, and cycle filters are widely attributed to him and used in algorithmic trading systems.
What to Know — Strengths and CriticismsStrengths: Ehlers’ approach is mathematically rigorous, explicitly uses engineering and DSP principles, and avoids “magic numbers” (like fixed-length 14-day RSI) by adapting to changing market cycles. This can produce more robust, adaptive trading indicators relative to standard ones.
Challenges / Criticisms: Some trading-community explorations of his systems (e.g. one based on his “Instantaneous Trendline” indicator) have shown poor performance with trend-following logic in out-of-sample backtests — leading some to invert the signal and use a mean-reversion logic instead.
This suggests that while the math or filtering ideas may be sound, actual trading success still depends heavily on how the filters/indicators are used, optimized, and tested — underscoring the need for rigorous backtesting and risk management.
Relevance & Influence — Why Traders Still Follow HimEhlers’ work helped popularize the use of DSP and adaptive filter design in trading tools, influencing many modern algorithmic traders, coders, and quantitative analysts.
Many “custom indicators” in trading platforms — especially those promising less lag and more responsiveness — trace their conceptual lineage to Ehlers’ research.
For traders with a coding background (e.g. using EasyLanguage, Python, or other algo-trading platforms), Ehlers’ papers and book content remain valuable as a mathematical foundation for building custom, tailored trading systems.
MESA (Maximum Entropy Spectrum Analysis)
Ehlers’ Instantaneous Trendline
Super Smoother Filter
Roofing Filter
Ehlers Sine Wave / Lead Sine
Fisher Transform (Ehlers Fisher)
Laguerre Filter / Laguerre RSI
Instantaneous Frequency & Hilbert Transform Tools
Mesa Adaptive Moving Average (MAMA) & FAMA
Decycler / De-Trending Indicator
Honorable Mentions