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John is an Electrical Engineer. He received his BSEE and MSEE from the University of Missouri and did his doctoral work at George Washington University, specializing in Fields & Waves and Information Theory. He has been a private trader since 1976, starting with fundamental analysis. With his engineering training he quickly gravitated to technical analysis of the market. He originally questioned what was magic about a 14 day RSI, or any other period. He concluded there was no unique answer and that variable market conditions must be measured for effective trading. He discovered Maximum Entropy Spectrum Analysis (MESA) while attending an Information Theory seminar in 1978. He has been a pioneer in introducing the MESA concept into technical analysis for the measurement of short term cycles. John has written the book "MESA, and Trading Market Cycles." He has written numerous articles for Futures and Stocks & Commodities magazines, and has spoken internationally on the subject of cycles in the market. He has now expanded the scope of his contributions to technical analysis through the application of scientific digital signal processing techniques.

Here's one of John Ehlers's recent presentations.

Rocket Science for Traders


Expert: John Ehlers
Type: PDF Workbook MP3 Audio
Running Time: 90 minutes
Workbook Length: 25 pages
Availability: Now
Average Rating:


In this session, John Ehlers teaches you to unleash the power of your computer by applying the science of modern digital signal processing to the art of trading. The result of this application is a series of indicators that operate together because they are adaptive to current market conditions. Computer code for all the indicators is provided.

Basic criteria are established for technical indicators, demonstrating their range and limitations. The concept of a Hilbert Transform is developed, and this transform is used to measure the dominant cycle and estimate the signal to noise ratio of the price data. The phase of the cyclic signal is extracted, and is used to derive a unique oscillator - The Sinewave Indicator. Additionally, the dominant cycle is removed from the data and the result is an Instantaneous Trendline. The way these new adaptive indicators work together is described.

The technical principles are applied specifically to several different kinds of stock trading systems. The advantages of using adaptive techniques in trading will be demonstrated.


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