MESA and Trading Market Cycles: Forecasting and Trading Strategies from the Creator of MESA
Makes one of the most popular tools of market analysis available to a wider audience of traders and technical analysts
Pioneered by John Ehlers in the late 1970s, the MESA method of price pattern analysis uses powerful wave theory analysis techniques, originally developed for the field of electrical engineering, to measure market cycles. MESA systems are currently used by technical analysts the world over. Top brokerages lease them and supply their clients with MESA signals and charts. And MESA systems consistently have been rated #1 by Futures Truth, the consumer reports organization of the futures industry. In this highly anticipated Second Edition of his classic work, Ehlers updates his MESA theories and makes them more accessible to a wider trading audience. Completely revised, featuring five new chapters, this new edition incorporates Ehlers's digital signal processing research into MESA. It also includes EasyLanguage programming code that makes it extremely easy for traders to take the leap from theory to practice.
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Why Cycles Exist in the Market
Principles of Cycles
Measuring Market Spectra
The Sinewave Indicator
10-bar cycle alpha amplitude Average trade bars c:\mesadll\mesa2kd.dll Chapter Chart created chart patterns coefficients cosine wave currentbar Cycle Mode cyclic DCPhase DCSine defineDllFunc described detrending Dominant Cycle period Drunkard's Walk EasyLanguage code elliptic filter equation Exponential Moving Average fast Fourier transform FIR filter float Fourier transform frequency components frequency response group delay Infinite Impulse Response input Instantaneous Trendline LeadSine Crosses low-frequency lag lpfloat MarketPosition Maximum drawdown measured cycle measured Dominant Cycle MESA algorithm momentum functions Normalized frequency Nyquist notch filter Number of trades Nyquist frequency observation period optimize output phase angle phasor price data Profit factor profit per trade quency random variable random walk rate of change RealPart short-term cycle shown in Figure signal sine Sinewave Indicator Smoothed Price spectral estimation spectrum Stochastic stock trading system Technical Analysis Telegrapher's Equation tion Total net profit TradeStation Trend Mode trend-following turning point waveform waveshape zero