|
|
|
|
MESA was first applied as an oil-exploration tool, drawing on the 1976 work of John Burg, a researcher who first developed and published the method. A common way of searching for oil is to set off explosions that send out sound bursts at known frequencies, and then "listen" to the echoes at different locations. Since oil-bearing and non-oil-bearing subterranean geologic formations reflect the sound differently, "maps" of an area’s subsurface geology can be created and likely oil deposits pinpointed.
The key information for mapping lies in the exact way that the principal frequencies of the explosions are modified by their underground travel. However, by the time the sound bursts from the explosions reach the listening sensors, their sound has been dampened and distorted by reflections and by passage through irregular bodies of sand, clay, water, different types of rock, and so on. The result is a burst of apparently chaotic noise. The challenge facing the prospecting geophysicists, then, is to pick out the now-faint principal frequencies from the jumbled noise recorded by their sensors, all within very short data samples due to the brevity of the explosions themselves.
MESA was the technique developed to accomplish this task. The geophysicists know the original frequencies emitted by the explosions, and they usually have an estimate of what the subsurface geology is and how it is likely to modify the original frequencies. Therefore, they can predict a range of frequencies where they expect to hear the principal sounds of the explosions. They then tell MESA to check different frequencies within that range, or beyond if necessary. Thanks to MESA’s sensitivity and ability to home in on cyclic data even in the presence of a large amount of chaotic "noise," they can then pick out just the principal sounds of the explosion, and analyze the modifications due to the geology, while discarding the jumbled echoes, reflections, and other sonic junk.
Radar Jamming
Later, defense-industry scientists discovered that MESA was a crucial tool for electronic countermeasures, and they gave it its first real-time application. Radar jamming is a vital weapon in modern air warfare—if a warplane can detect and analyze the radar signals of another aircraft, a missile, or a ground installation, then it can defend itself by emitting signals that confuse or deceive the enemy’s listening radar receivers.
Initially, the challenge was to quickly tune in to the fixed frequencies of older radars, and then start jamming on those frequencies. However, as radar became more sophisticated and made increasing use of powerful computers, they became harder to tune in on: irregular noise was superimposed on the radar signals to cloak them, the signals were broken up into bursts too short for older jammers to analyze, and the frequencies used were varied rapidly and constantly, making it difficult for would-be jammers to detect a signal at all.
Radar scientists recognized that MESA techniques could solve these problems. MESA’s ability to filter out cyclical activity from background noise handled the cloaking transmissions; and its ability to find cyclical signals based on a very short data samples meant that it could both detect short bursts of radar, and cope with rapidly changing frequencies. So MESA’s methods were coupled with full-spectrum scanning and jamming transmitters to quickly lock in on and jam even the trickiest, most quickly varying radar signals.
The same features that led to MESA’s use in oil exploration and radar jamming, developed through the efforts of mathematicians, geophysicists, and radar scientists, are the ones that equip MESA so well to quickly filter cyclic components from incoming market price data, and respond with a potentially profitable prediction.
John Ehlers served in the U. S. Air Force in electronic countermeasures during the Korean War, which led him to obtain his bachelor’s, master’s and doctorate degrees in the field of communication engineering and information theory. His continuing work in radar jamming research introduced him to MESA, and thanks to his curiosity and interest in trading, led to the application of MESA techniques to market analysis and to MESA Studies on Aspen Graphics.
MESA & Fourier Analysis
MESA, which stands for Maximum Entropy Spectrum Analysis, is an advanced mathematical method for filtering any cyclical components of different frequencies from complex signals or data sets. MESA has been used to identify the cyclic components of data sets that originate from chaotic bursts of radio waves, subterranean explosions, and, more recently, from military radar. An outgrowth of the scientific and engineering technique of Fourier analysis, MESA makes a radical break from earlier cycle-detection methods.
Traditional Fourier techniques such as the fast Fourier transform identify cycles with a high degree of certainty, but require very large data samples—an integral multiple of the wavelength of the cycle or cycles detected. Furthermore, even larger data samples are required to allow "
good resolution"—identification of concurrent cycles of unrelated wavelengths. These restrictions render traditional Fourier methods impractical for real-time market applications because cycles recurring over a long period tend to be apparent on a bar chart, without the aid of complex mathematics.
MESA, by contrast, focuses on the identification of the maximum amount of cyclic activity in a very short data sample. Whereas Fourier techniques work best for identifying cycles whose wavelengths are a tiny fraction of the length of the data samples, MESA can find a cycle in a sample only as long as the wavelength itself. This sensitivity equips MESA uniquely to pick out market cycles as they develop in fast-moving markets.
John F. Ehlers, a Ph.D. holder in electrical engineering and radar-jamming scientist, is the pioneer and acknowledged authority in applying MESA for trading purposes. His MESA end-of-day trading program was the first of its type. It is with his cooperation and supervision that MESA studies have been incorporated in Aspen Graphics, in their first and only real-time implementation.
For a more complete exposition of the development, mathematics, and particular characteristics of MESA, refer to Ehlers’ authoritative book MESA and Trading Market Cycles.