The encyclopedia of trading strategies:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
McGraw-Hill
2000
|
| Schriftenreihe: | The Irwin trader's edge series
|
| Schlagworte: | |
| Online-Zugang: | Publisher description Table of contents Inhaltsverzeichnis |
| Beschreibung: | XXI, 376 S. graph. Darst. |
| ISBN: | 0070580995 |
Internformat
MARC
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| 245 | 1 | 0 | |a The encyclopedia of trading strategies |c Jeffrey Owen Katz ; Donna L. McCormick |
| 264 | 1 | |a New York [u.a.] |b McGraw-Hill |c 2000 | |
| 300 | |a XXI, 376 S. |b graph. Darst. | ||
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| 650 | 7 | |a Effectenhandel |2 gtt | |
| 650 | 7 | |a Futures |2 gtt | |
| 650 | 7 | |a Termijnhandel |2 gtt | |
| 650 | 4 | |a Commodity futures | |
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Datensatz im Suchindex
| _version_ | 1804127886082310144 |
|---|---|
| adam_text | CONTENTS PREFACE xiii
INTRODUCTION xv
What Is a Complete Mechanical Trading System? • What Are Good Entries and Exits?
• The Scientific Approach to System Development • Tools and Materials Needed for
the Scientific Approach
PARTI
Tools of the Trade
Introduction 1
Chapter 1
Data 3
Types of Data • Data Time Frames • Data Quality • Data Sources and Vendors
Chapter 2
Simulators 13
Types of Simulators • Programming the Simulator • Simulator Output (performance
summary reports; trade by trade reports) • Simulator Performance (speed; capacity;
power) • Reliability of Simulators • Choosing the Right Simulator • Simulators Used
in This Book
Chapter 3
Optimizers and Optimization 29
What Optimizers Do • How Optimizers Are Used • Types of Optimization (implicit
optimizers; brute force optimizers; user guided optimization; genetic optimizers; optimization
by simulated annealing; analytic optimizers; linear programming) • How to Fail with
Optimization (small samples; large parameter sets; no verification) • How to Succeed
with Optimization (large, representative samples; few rules and parameters; verification
of results) • Alternatives to Traditional Optimization • Optimizer Tools and Information •
Which Optimizer Is for You?
CONTENTS
Chapter 4
Statistics 51
Why Use Statistics to Evaluate Trading Systems? • Sampling • Optimization and
Curve Fitting • Sample Size and Representativeness • Evaluating a System Statistically
• Example 1: Evaluating the Out of Sample Test (what if the distribution is not normal?
what if there is serial dependence? what if the markets change?) • Example 2:
Evaluating the In Sample Tests • Interpreting the Example Statistics (optimization
results; verification results) • Other Statistical Techniques and Their Use (genetically
evolved systems; multiple regression; monte carlo simulations; out of sample testing;
walk forward testing) • Conclusion
PARTn
The Study of Entries
Introduction 71
What Constitutes a Good Entry? • Orders Used in Entries (stop orders; limit orders;
market orders; selecting appropriate orders) • Entry Techniques Covered in This Book
(breakouts and moving averages; oscillators; seasonality; lunar and solar phenomena;
cycles and rhythms; neural networks; genetically evolved entry rules) • Standardized
Exits • Equalization of Dollar Volatility • Basic Test Portfolio and Platform
Chapter 5
Breakout Models 83
Kinds of Breakouts • Characteristics of Breakouts • Testing Breakout Models •
Channel Breakout Entries (close only channel breakouts; highest highAowest low
breakouts) • Volatility Breakout Entries • Volatility Breakout Variations (long positions
only; currencies only; adx trend filter) • Summary Analyses (breakout types; entry
orders; interactions; restrictions and filters; analysis by market) • Conclusion •
What Have We Learned?
Chapter 6
Moving Average Models 109
What is a Moving Average? • Purpose of a Moving Average • The Issue of Lag •
Types of Moving Averages • Types of Moving Average Entry Models • Characteristics
of Moving Average Entries • Orders Used to Effect Entries • Test Methodology •
Tests of Trend Following Models • Tests of Counter Trend Models • Conclusion •
What Have We Learned?
CONTENTS Ix
Chapter 7
Oscillator Based Entries 133
What Is an Oscillator? • Kinds of Oscillators • Generating Entries with Oscillators •
Characteristics of Oscillator Entries • Test Methodology • Test Results (tests of
overbought/oversold models; tests of signal line models; tests of divergence models;
summary analyses) • Conclusion • What Have We Learned?
Chapter 8
Seasonality 153
What Is Seasonality? • Generating Seasonal Entries • Characteristics of Seasonal
Entries • Orders Used to Effect Seasonal Entries • Test Methodology • Test Results
(test of the basic crossover model; tests of the basic momentum model; tests of the
crossover model with confirmation; tests of the crossover model with confirmation and
inversions; summary analyses) • Conclusion • What Have We Learned?
Chapter 9
Lunar and Solar Rhythms 179
Legitimacy or Lunacy? • Lunar Cycles and Trading (generating lunar entries; lunar test
methodology; lunar test results; tests of the basic crossover model; tests of the basic
momentum model; tests of the crossover model with confirmation; tests of the crossover
model with confirmation and inversions; summary analyses; conclusion) • Solar
Activity and Trading (generating solar entries; solar test results; conclusion) •
What Have We Learned?
Chapter 10 Cycle Based Entries 203
Cycle Detection Using MESA • Detecting Cycles Using Filter Banks (butterworth
filters; wavelet based filters) • Generating Cycle Entries Using Filter Banks •
Characteristics of Cycle Based Entries • Test Methodology • Test Results •
Conclusion • What Have We Learned?
Chapter 11 Neural Networks 227
What Are Neural Networks? (feed forward neural networks) • Neural Networks
in Trading • Forecasting with Neural Networks • Generating Entries with Neural
Predictions • Reverse Slow %K Model (code for the reverse slow %k model; test
methodology for the reverse slow %k model; training results for the reverse slow %k
model) • Turning Point Models (code for the turning point models; test methodology
CONTENTS
for the turning point models; training results for the turning point models) • Trading
Results for All Models (trading results for the reverse slow %k model; trading results
for the bottom turning point model; trading results for the top turning point model) •
Summary Analyses • Conclusion • What Have We Learned?
Chapter 12
Genetic Algorithms 257
What Are Genetic Algorithms? • Evolving Rule Based Entry Models • Evolving an
Entry Model {the rule templates) • Test Methodology (code for evolving an entry
model) • Test Results (solutions evolved for long entries; solutions evolved for short
entries; test results for the standard portfolio; market by market test results; equity
curves; the rules for the solutions tested) • Conclusion • What Have We Learned?
PARTm The Study of Exits
Introduction 281
The Importance of the Exit • Goals of a Good Exit Strategy • Kinds of Exits
Employed in an Exit Strategy (money management exits; trailing exits; profit target
exits; time based exits; volatility exits; barrier exits; signal exits) • Considerations
When Exiting the Market (gunning; trade offs with protective stops; slippage;
contrarian trading; conclusion) • Testing Exit Strategies • Standard Entries for Testing
Exits (the random entry model)
Chapter 13
The Standard Exit Strategy 293
What is the Standard Exit Strategy? • Characteristics of the Standard Exit • Purpose of
Testing the SES • Tests of the Original SES (test results) • Tests of the Modified SES
(test results) • Conclusion • What Have We Learned?
Chapter 14
Improvements on the Standard Exit 309
Purpose of the Tests • Tests of the Fixed Stop and Profit Target • Tests of Dynamic
Stops (test of the highest high/lowest low stop; test of the dynamic atr based stop; test
of the modified exponential moving average dynamic stop) • Tests of the Profit Target •
Test of the Extended Time Limit • Market By Market Results for the Best Exit •
Conclusion • What Have We Learned?
CONTENTS xi
Chapter 15
Adding Artificial Intelligence to Exits 335
Test Methodology for the Neural Exit Component • Results of the Neural Exit Test
(baseline results; neural exit portfolio results; neural exit market by market results) •
Test Methodology for the Genetic Exit Component (top 10 solutions with baseline exit;
results of rule based exits for longs and shorts; market by market results of rule based
exits for longs; market by market results of rule based exits for shorts) • Conclusion •
What Have We Learned?
Conclusion 353
The Big Picture • Points of Light • Looking into the Light
Notice 362
Companion Software Available
Appendix 363
References and Suggested Reading
INDEX 367
|
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| language | English |
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| title | The encyclopedia of trading strategies |
| title_auth | The encyclopedia of trading strategies |
| title_exact_search | The encyclopedia of trading strategies |
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| title_fullStr | The encyclopedia of trading strategies Jeffrey Owen Katz ; Donna L. McCormick |
| title_full_unstemmed | The encyclopedia of trading strategies Jeffrey Owen Katz ; Donna L. McCormick |
| title_short | The encyclopedia of trading strategies |
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