Cybernetic trading strategies: developing a profitable trading system with state-of-the-art technologies
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | Undetermined |
| Veröffentlicht: |
New York <<[u.a.]>>
Wiley
1997
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| Schriftenreihe: | Wiley trading advantage
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 315 S. zahlr. graph. Darst. |
| ISBN: | 0471149209 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents
Introduction 1
PART ONE CLASSICAL MARKET PREDICTION
1 Classical Intermarket Analysis as a Predictive Tool 9
What Is Intermarket Analysis? 9
Using Intermarket Analysis to Develop Filters and Systems 27
Using Intermarket Divergence to Trade the S P500 29
Predicting T-Bonds with Intermarket Divergence 32
Predicting Gold Using Intermarket Analysis 35
Using Intermarket Divergence to Predict Crude 36
Predicting the Yen with T-Bonds 38
Using Intermarket Analysis on Stocks 39
2 Seasonal Trading 42
Types of Fundamental Forces 42
Calculating Seasonal Effects 43
Measuring Seasonal Forces 43
The Ruggiero/Barna Seasonal Index 45
Static and Dynamic Seasonal Trading 45
Judging the Reliability of a Seasonal Pattern 46
Counterseasonal Trading 47
xv
xvi Contents
Conditional Seasonal Trading 47
Other Measurements for Seasonality 48
Best Long and Short Days of Week in Month 49
Trading Day-of-Month Analysis 51
Day-of-Year Seasonality 52
Using Seasonality in Mechanical Trading Systems 53
Counterseasonal Trading 55
3 Long-Term Patterns and Market Timing for Interest
Rates and Stocks 60
Inflation and Interest Rates 60
Predicting Interest Rates Using Inflation 62
Fundamental Economic Data for Predicting Interest Rates 63
A Fundamental Stock Market Timing Model 68
4 Trading Using Technical Analysis 70
Why Is Technical Analysis Unjustly Criticized? 70
Profitable Methods Based on Technical Analysis 73
5 The Commitment of Traders Report 86
What Is the Commitment of Traders Report? 86
How Do Commercial Traders Work? 87
Using the COT Data to Develop Trading Systems 87
PART TWO STATISTICALLY BASED MARKET PREDICTION
6 A Trader s Guide to Statistical Analysis 95
Mean, Median, and Mode 96
Types of Distributions and Their Properties 96
The Concept of Variance and Standard Deviation 98
How Gaussian Distribution, Mean, and Standard
Deviation Interrelate 98
Statistical Tests Value to Trading System Developers 99
Correlation Analysis 101
7 Cycle-Based Trading 103
The Nature of Cycles 105
Cycle-Based Trading in the Real World 108
Contents xvii
Using Cycles to Detect When a Market Is Trending 109
Adaptive Channel Breakout 114
Using Predictions from MEM for Trading 115
8 Combining Statistics and Intermarket Analysis 119
Using Correlation to Filter Intermarket Patterns 119
Predictive Correlation 123
Using the CRB and Predictive Correlation to Predict Gold 124
Intermarket Analysis and Predicting the Existence of a Trend 126
9 Using Statistical Analysis to Develop Intelligent Exits 130
The Difference between Developing Entries and Exits 130
Developing Dollar-Based Stops 131
Using Scatter Charts of Adverse Movement to Develop Stops 132
Adaptive Stops 137
10 Using System Feedback to Improve Trading
System Performance 140
How Feedback Can Help Mechanical Trading Systems 140
How to Measure System Performance for Use as Feedback 141
Methods of Viewing Trading Performance for Use as Feedback 141
Walk Forward Equity Feedback 142
How to Use Feedback to Develop Adaptive Systems or Switch
between Systems 147
Why Do These Methods Work? 147
11 An Overview of Advanced Technologies 149
The Basics of Neural Networks 149
Machine Induction Methods 153
Genetic Algorithms—An Overview 160
Developing the Chromosomes 161
Evaluating Fitness 162
Initializing the Population 163
The Evolution 163
Updating a Population 168
Chaos Theory 168
Statistical Pattern Recognition 171
Fuzzy Logic 172
xviii Contents
PART THREE MAKING SUBJECTIVE METHODS MECHANICAL
12 How to Make Subjective Methods Mechanical 179
Totally Visual Patterns Recognition 180
Subjective Methods Definition Using Fuzzy Logic 180
Human-Aided Semimechanical Methods 180
Mechanically Definable Methods 183
Mechanizing Subjective Methods 183
13 Building the Wave 184
An Overview of Elliott Wave Analysis 184
Types of Five-Wave Patterns 186
Using the Elliott Wave Oscillator to Identify the Wave Count 187
TradeStation Tools for Counting Elliott Waves 188
Examples of Elliott Wave Sequences Using Advanced GET 194
14 Mechanically Identifying and Testing Candlestick Patterns 197
How Fuzzy Logic Jumps Over the Candlestick 197
Fuzzy Primitives for Candlesticks 199
Developing a Candlestick Recognition Utility Step-by-Step 200
PART FOUR TRADING SYSTEM DEVELOPMENT AND TESTING
15 Developing a Trading System 209
Steps for Developing a Trading System 209
Selecting a Market for Trading 209
Developing a Premise 211
Developing Data Sets 211
Selecting Methods for Developing a Trading System 212
Designing Entries 214
Developing Filters for Entry Rules 215
Designing Exits 216
Parameter Selection and Optimization 217
Understanding the System Testing and Development Cycle 217
Designing an Actual System 218
16 Testing, Evaluating, and Trading a Mechanical
Trading System 225
The Steps for Testing and Evaluating a Trading System 226
Testing a Real Trading System 231
Contents xix
PART FIVE USING ADVANCED TECHNOLOGIES TO DEVELOP
TRADING STRATEGIES
17 Data Preprocessing and Postprocessing 241
Developing Good Preprocessing—An Overview 241
Selecting a Modeling Method 243
The Life Span of a Model 243
Developing Target Output(s) for a Neural Network 244
Selecting Raw Inputs 248
Developing Data Transforms 249
Evaluating Data Transforms 254
Data Sampling 257
Developing Development, Testing, and Out-of-Sample Sets 257
Data Postprocessing 258
18 Developing a Neural Network Based on Standard
Rule-Based Systems 259
A Neural Network Based on an Existing Trading System 259
Developing a Working Example Step-by-Step 264
19 Machine Learning Methods for Developing
Trading Strategies 280
Using Machine Induction for Developing Trading Rules 281
Extracting Rules from a Neural Network 283
Combining Trading Strategies 284
Postprocessing a Neural Network 285
Variable Elimination Using Machine Induction 286
Evaluating the Reliability of Machine-Generated Rules 287
20 Using Genetic Algorithms for Trading Applications 290
Uses of Genetic Algorithms in Trading 290
Developing Trading Rules Using a Genetic Algorithm—
An Example 293
References and Readings 307
Index 310
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| id | DE-604.BV026176903 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T23:06:38Z |
| institution | BVB |
| isbn | 0471149209 |
| language | Undetermined |
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| physical | XIX, 315 S. zahlr. graph. Darst. |
| publishDate | 1997 |
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| publisher | Wiley |
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| series2 | Wiley trading advantage |
| spelling | Ruggiero, Murray A. Verfasser aut Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies Murray A. Ruggiero New York <<[u.a.]>> Wiley 1997 XIX, 315 S. zahlr. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Wiley trading advantage Finanzanalyse (DE-588)4133000-6 gnd rswk-swf Computerunterstütztes Verfahren (DE-588)4139030-1 gnd rswk-swf Anlagepolitik (DE-588)4206018-7 gnd rswk-swf Anlagepolitik (DE-588)4206018-7 s Finanzanalyse (DE-588)4133000-6 s Computerunterstütztes Verfahren (DE-588)4139030-1 s DE-188 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=021761797&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ruggiero, Murray A. Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies Finanzanalyse (DE-588)4133000-6 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Anlagepolitik (DE-588)4206018-7 gnd |
| subject_GND | (DE-588)4133000-6 (DE-588)4139030-1 (DE-588)4206018-7 |
| title | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies |
| title_auth | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies |
| title_exact_search | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies |
| title_full | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies Murray A. Ruggiero |
| title_fullStr | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies Murray A. Ruggiero |
| title_full_unstemmed | Cybernetic trading strategies developing a profitable trading system with state-of-the-art technologies Murray A. Ruggiero |
| title_short | Cybernetic trading strategies |
| title_sort | cybernetic trading strategies developing a profitable trading system with state of the art technologies |
| title_sub | developing a profitable trading system with state-of-the-art technologies |
| topic | Finanzanalyse (DE-588)4133000-6 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd Anlagepolitik (DE-588)4206018-7 gnd |
| topic_facet | Finanzanalyse Computerunterstütztes Verfahren Anlagepolitik |
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