Cycle Analytics for Traders E-Book

John F. Ehlers

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Wiley Trading Series
• Sprache: Englisch

Seitenzahl: 265

Veröffentlichungsjahr: 2013

Beschreibung

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

Leseprobe

CYCLE ANALYTICSFORTRADERS

CYCLE ANALYTICSFOR TRADERS

Advanced Technical Trading Concepts

John F. Ehlers

Cover image: Chart © iStockphoto.com/Andrey Prokhorov Cover design: Wiley

Copyright © 2013 by John F. Ehlers. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, [phone], fax [phone], or on the Web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, [phone], fax [phone], or online at www.wiley.com/go/permissions.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at [phone], outside the United States at [phone] or fax [phone].

Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com. For more information about Wiley products, visit www.wiley.com.

Library of Congress Cataloging-in-Publication Data:

Ehlers, John F., 1933- Cycle analytics for traders : advanced technical trading concepts / John F. Ehlers. pages cm ISBN 978-1-118-72851-2 (cloth) — ISBN 978-1-118-72841-3 (ebk) — ISBN 978-1-118-72860-4 (ebk) 1. Technical analysis (Investment analysis) 2. Investment analysis. I. Title. HG4529.E388 2014 332.63′2042 — dc23

2013034306

CONTENTS

Cover

Half Title

Title Page

Copyright Page

Preface

About the Author

Chapter 1: Unified Filter Theory

Transfer Response

Nonrecursive Filters

Recursive Filters

Generalized Filters

Programming the Filters

Wave Amplitude, Power, and Decibels (dB)

Key Points to Remember

Chapter 2: SMAs, EMAs, or Other?

Simple Moving Averages (SMAs)

Exponential Moving Averages (EMAs)

Weighted Moving Averages (WMAs)

Median Filter

Key Points to Remember

Chapter 3: Smoothing Filters on Steroids

Nonrecursive Filters

Modified Simple Moving Averages

Modified Least-Squares Quadratics

SuperSmoother

SuperSmoother Filter Applications

Key Points to Remember

Chapter 4: Decyclers

Decycler Construction

Decycler Application

Decycler Oscillator

Key Points to Remember

Chapter 5: Band-Pass Filters

Band-Pass Filter

Band-Pass Filter Q

Automatic Gain Control (AGC)

Spectral Dilation Removal

Band-Pass Filter

Measuring the Cycle Period

Key Points to Remember

Chapter 6: Market Structure and the Hurst Coefficient

Fractal Dimension

Computing the Hurst Coefficient

The Hurst Coefficient in Action

Drunkard's Walk Hypothesis for Market Structure

Key Points to Remember

Chapter 7: Spectral Dilation

Frequency Content of Indicator Outputs

Roofing Filter as an Indicator

Impact of Spectral Dilation on Conventional Indicators

Key Points to Remember

Chapter 8: Autocorrelation

Background

Autocorrelation

Autocorrelation Periodogram

Autocorrelation Reversals

Key Points to Remember

Chapter 9: Fourier Transforms

Spectral Dilation

Discrete Fourier Transform (DFT)

Key Points to Remember

Chapter 10: Comb Filter Spectral Estimates

Spectral Dilation

Computing a Comb Filter Spectral Estimate

Key Points to Remember

Chapter 11: Adaptive Filters

Adaptive Relative Strength Index (RSI)

Adaptive Stochastic Indicator

Adaptive CCI (Commodity Channel Index)

Adaptive Band-Pass Filter

Adaptive Indicator Comparison

Key Points to Remember

Chapter 12: The Even Better Sinewave Indicator

Even Better Sinewave Approach

Even Better Sinewave Description

Using the Even Better Sinewave Indicator

Key Points to Remember

Chapter 13: Convolution

Theoretical Foundation

Heat Map Display

Computing Convolution

Key Points to Remember

Chapter 14: The Hilbert Transformer

Analytic Signals

Hilbert Transformer Mathematics

Computing the Hilbert Transformer

The Hilbert Transformer Indicator

Using the Hilbert Transformer to Compute the Dominant Cycle

Dual Differentiator

Phase Accumulation

Homodyne

Key Points to Remember

Chapter 15: Indicator Transforms

Fisher Transform

Inverse Fisher Transform

Cube Transform

Key Points to Remember

Chapter 16: SwamiCharts

SwamiCharts Overview

SwamiCharts RSI

SwamiCharts Stochastic

Roll Your Own SwamiCharts

Key Points to Remember

Chapter 17: Swing-Trading Strategies

Conventional Wisdom

Anticipating the Turning Point

Sine Wave Uniqueness

Safety Valve

Exiting a Trade

Stop Loss

Evaluating a Trading Strategy

Monte Carlo Evaluation

StockSpotter.com

Key Points to Remember

About the Website

Index

Book Card

PREFACE

It has been over 10 years since Rocket Science for Traders was published. In those days, technical analysis was primarily the province of futures traders, while portfolio theory and fundamental analysis comprised the conventional wisdom for equity traders. However, there have been profound changes in the marketplace since that time. Futures trading has lost popularity because of scandals involving segregated customer accounts, the stock market's relentless trend upward has been broken with the result that buy-and-hold is no longer a valid investment strategy, and new trading vehicles such as exchange-traded funds (ETFs) have evolved. In addition, commission rates have decreased, and the Internet has made electronic trading available to everyone. All this has caused investors to be more involved in the trading process and interested in self-directed trading. Major brokerage houses have responded by including technical analysis tools in their trading platforms.

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 rather than to use the trading tools on blind faith. 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. The concepts are presented so they can be understood with only a background in algebra. The writing style in the book is intentionally terse so the reader doesn't need to wade through a mountain of words to find the ideas being presented. EasyLanguage computer code is used to calculate and display the indicators. From my viewpoint, Easy­Language is just a dialect of Pascal with key words for trading. Therefore, the code should be nearly as readable as English.

Cycles are unique because they are one of the few characteristics of market data that can be scientifically measured. However, cycle measurement is extremely complex. In the most general sense, there is a triple infinity of parameters–period, phase, and amplitude–that must be identified simultaneously to completely describe the cycles. Additionally, market cycles are ephemeral and are often buried in pure noise. So the compromises begin. One of the first realizations that a trader must make is that cycles cannot be the basis of trades all the time. Sometimes the cycle swings are swamped by trends, and it is folly to try to fight the trend. However, the cyclic swings can be helpful to know when to buy on a dip in the direction of the trend. Traditional indicators such as Stochastics, relative strength index (RSI), moving average convergence/divergence (MACD), and commodity channel index (CCI) are subject to the same constraints, and therefore this book will lead to a greater understanding of all technical indicators.

Most important, 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. The descriptions are written for understanding at several different levels. Traders with little mathematical background will be able to assess general market conditions to their advantage. More technically advanced traders will be able to create indicators and strategies that automatically adapt to measured market conditions by using combinations of computer code that are described.

So what should a trader take away from this book? These are a few of the new concepts that I have ranked in priority:

An awareness of Spectral Dilation, and how to eliminate it or to use it to your advantage.How to use automatic gain control (AGC) to normalize indicator amplitude swings.Thinking of prices in the frequency domain as well as in the time domain.An awareness that all indicators are statistical rather than absolute, as implied by their single-line displays.Several advanced cookbook filters. These include the SuperSmoother, roofing filter, even better sinewave, decycler, and Hilbert Transform ­Indicator.Several different methods of estimating market spectra and sifting out the dominant cycle, with the autocorrelation periodogram being the preferred method.How to use transforms to improve the display and interpretation of indicators.

The concepts I have developed and derived from scientific principles are new and useful aids to short-term trading. Ultimately, trading comes down to buying and selling decisions. These decisions are never easy, and in the final chapter I unite the concepts with a few tips and tricks that I have acquired in my years of trading. Above all, trading should be approached as a statistical process. Even with a good performance of 60 percent winning trades, 60 percent is a lot closer to 50–50 than it is to 100 percent regarding a single event. Therefore, the performance judged by a few trades is invalid, and I would encourage readers to stick with a trading strategy they have developed with a profitable history, albeit hypothetical, and let the statistics be the light to success in the long run.

As evidence of my warped sense of humor, each chapter starts with a “Tom Swifty” pun that encapsulates the entire content of the chapter and I hope serves as an anchor for the reader's memory. I think the computer code is often the most succinct and efficient method of describing a concept. Accordingly, my style is to be brief, with plenty of poetic license with mathematical notation in an effort to convey the concepts to most traders. Each chapter concludes with the significant points to remember from that chapter.

I wish you all good trading.

John F. Ehlers August 2013

ABOUT THE AUTHOR

John Ehlers is an electrical engineer, receiving his BSEE and MSEE from the University of Missouri. He did his doctoral work at The George ­Washington University, specializing in Fields & Waves and Information Theory. He has retired as a senior engineering fellow from Raytheon. He has been a private trader since 1976.

John is a pioneer in introducing the MESA cycles-measuring algorithm and the use of digital signal processing in technical analysis. He developed maximum entropy spectrum analysis (MESA) over three decades ago. The program has evolved with the increased capacity of modern computers.

John has written extensively about quantitative algorithmic trading ­using advanced DSP (digital signal processing) and has spoken internationally on the subject. His books include MESA and Trading Market Cycles, Rocket ­Science for Traders, and Cybernetic Analysis for Stocks and Futures. His approach is unique. Any technique must first work on theoretical waveforms before testing against real-world data is attempted.

John is a cofounder of StockSpotter.com.