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Cycle Analytics for Traders

A technical resource for self-directed traders who want to understand the scientific underpinnings of the filters and indicators used in trading decisions This is a technical resource book written for self-directed traders who want to understand the scientific underpinnings of the filters and indicators they use in their trading decisions. There is plenty of theory and years of research behind the unique solutions provided in this book, but the emphasis is on simplicity rather than mathematical purity. In particular, the solutions use a pragmatic approach to attain effective trading results. Cycle Analytics for Traders will allow traders to think of their indicators and trading strategies in the frequency domain as well as their motions in the time domain. This new viewpoint will enable them to select the most efficient filter lengths for the job at hand. Shows an awareness of Spectral Dilation, and how to eliminate it or to use it to your advantage Discusses how to use Automatic Gain Control (AGC) to normalize indicator amplitude swings Explains thinking of prices in the frequency domain as well as in the time domain Creates an awareness that all indicators are statistical rather than absolute, as implied by their single line displays Sheds light on several advanced cookbook filters Showcases new advanced indicators like the Even Better Sinewave and Decycler Indicators Explains how to use transforms to improve the display and interpretation of indicators
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Table of Contents

Preface ix About the Author xiii Chapter 1 Unified Filter Theory 1 Transfer Response 1 Nonrecursive Filters 3 Recursive Filters 8 Generalized Filters 10 Programming the Filters 11 Wave Amplitude, Power, and Decibels (dB) 13 Key Points to Remember 13 Chapter 2 SMAs, EMAs, or Other? 15 Simple Moving Averages (SMAs) 15 Exponential Moving Averages (EMAs) 18 Weighted Moving Averages (WMAs) 21 Median Filter 22 Key Points to Remember 23 Chapter 3 Smoothing Filters on Steroids 25 Nonrecursive Filters 25 Modified Simple Moving Averages 29 Modified Least-Squares Quadratics 30 SuperSmoother 31 SuperSmoother Filter Applications 34 Key Points to Remember 36 Chapter 4 Decyclers 39 Decycler Construction 39 Decycler Application 41 Decycler Oscillator 43 Key Points to Remember 45 Chapter 5 Band-Pass Filters 47 Band-Pass Filter 47 Band-Pass Filter Q 51 Automatic Gain Control (AGC) 54 Spectral Dilation Removal 56 Band-Pass Filter 56 Measuring the Cycle Period 58 Key Points to Remember 61 Chapter 6 Market Structure and the Hurst Coefficient 63 Fractal Dimension 65 Computing the Hurst Coefficient 67 The Hurst Coefficient in Action 68 Drunkard s Walk Hypothesis for Market Structure 70 Key Points to Remember 74 Chapter 7 Spectral Dilation 77 Frequency Content of Indicator Outputs 77 Roofing Filter as an Indicator 80 Impact of Spectral Dilation on Conventional Indicators 83 Key Points to Remember 88 Chapter 8 Autocorrelation 91 Background 91 Autocorrelation 93 Autocorrelation Periodogram 102 Autocorrelation Reversals 110 Key Points to Remember 113 Chapter 9 Fourier Transforms 115 Spectral Dilation 116 Discrete Fourier Transform (DFT) 117 Key Points to Remember 124 Chapter 10 Comb Filter Spectral Estimates 125 Spectral Dilation 125 Computing a Comb Filter Spectral Estimate 126 Key Points to Remember 133 Chapter 11 Adaptive Filters 135 Adaptive Relative Strength Index (RSI) 135 Adaptive Stochastic Indicator 142 Adaptive CCI (Commodity Channel Index) 147 Adaptive Band-Pass Filter 152 Adaptive Indicator Comparison 157 Key Points to Remember 158 Chapter 12 The Even Better Sinewave Indicator 159 Even Better Sinewave Approach 160 Even Better Sinewave Description 160 Using the Even Better Sinewave Indicator 162 Key Points to Remember 164 Chapter 13 Convolution 165 Theoretical Foundation 165 Heat Map Display 168 Computing Convolution 169 Key Points to Remember 174 Chapter 14 The Hilbert Transformer 175 Analytic Signals 176 Hilbert Transformer Mathematics 177 Computing the Hilbert Transformer 181 The Hilbert Transformer Indicator 183 Using the Hilbert Transformer to Compute the Dominant Cycle 186 Dual Differentiator 187 Phase Accumulation 189 Homodyne 192 Key Points to Remember 194 Chapter 15 Indicator Transforms 195 Fisher Transform 195 Inverse Fisher Transform 198 Cube Transform 200 Key Points to Remember 202 Chapter 16 SwamiCharts 203 SwamiCharts Overview 204 SwamiCharts RSI 205 SwamiCharts Stochastic 210 Roll Your Own SwamiCharts 216 Key Points to Remember 216 Chapter 17 Swing-Trading Strategies 217 Conventional Wisdom 219 Anticipating the Turning Point 220 Sine Wave Uniqueness 221 Safety Valve 224 Exiting a Trade 225 Stop Loss 225 Evaluating a Trading Strategy 226 Monte Carlo Evaluation 227 228 Key Points to Remember 229 About the Website 231 Index 233

About the Author

John F. Ehlers worked as an electrical engineer at one of the largest aerospace companies in the industry before retiring as a senior engineering fellow. A graduate of the University of Missouri, he has been a private trader since 1976, specializing in technical analysis. The discoverer of Maximum Entropy Spectrum Analysis, he writes extensively on technical trading and speaks internationally on the subject.

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