John F. Ehlers

Cycle Analytics for Traders, + Downloadable Software

Advanced Technical Trading Concepts

• Gebundenes Buch

Produktbeschreibung

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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Produktdetails

• Wiley Trading Series
• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 256
• Erscheinungstermin: 18. November 2013
• Englisch
• Abmessung: 236mm x 156mm x 27mm
• Gewicht: 457g
• ISBN-13: 9781118728512
• ISBN-10: 1118728513
• Artikelnr.: 38056390

Autorenporträt

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.

Inhaltsangabe

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
Stockspotter.com 228
Key Points to Remember 229
About the Website 231
Index 233