Book description
"The computer can do more than show us pretty pictures. [It] can optimize, backtest, prove or disprove old theories, eliminate the bad ones and make the good ones better. Cybernetic Trading Strategies explores new ways to use the computer and finds ways to make a valuable machine even more valuable." --from the Foreword by John J. Murphy.
Until recently, the computer has been used almost exclusively as a charting and data-gathering tool. But as traders and analysts have quickly discovered, its capabilities are far more vast. Now, in this groundbreaking new book, Murray Ruggiero, a leading authority on cybernetic trading systems, unlocks their incredible potential and provides an in-depth look at the growing impact of advanced technologies on intermarket analysis. A unique resource, Cybernetic Trading Strategies provides specific instructions and applications on how to develop tradable market timing systems using neural networks, fuzzy logic, genetic algorithms, chaos theory, and machine induction methods.
Currently utilized by some of the most powerful financial institutions in the world--including John Deere and Fidelity Investments--today's advanced technologies go beyond subjective interpretations of market indicators to enhance traditional analysis. As a result, existing trading systems gain a competitive edge. Ruggiero reveals how "incorporating elements of statistical analysis, spectral analysis, neural networks, genetic algorithms, fuzzy logic, and other high-tech concepts into a traditional technical trading system can greatly improve the performance of standard trading systems." For example: spectral analysis can be used to detect when a market is trending earlier than classical indicators such as ADX.
Drawing on his extensive research on market analysis, Ruggiero provides an incisive overview of cyber-systems--systems that, when applied correctly, can increase trading returns by as much as 200% to 300%. The author covers a wide range of important topics, examining classical technical analysis methodologies and seasonal trading, as well as statistically based market prediction and the mechanization of subjective methods such as candlestick charts and the Elliott Wave. Precise explanations and dozens of real-world examples show you how to:
Incorporate advanced technologies into classical technical analysis methodologies.
Identify which of these technologies have the most market applicability.
Build trading systems to maximize reliability and profitability based on your own risk/reward criteria.
Most importantly, Cybernetic Trading Strategies takes you step by step through system testing and evaluation, a crucial step for controlling risk and managing money.
With up-to-date information from one of the field's leading authorities, Cybernetic Trading Strategies is the definitive guide to developing, implementing, and testing today's cutting-edge computer trading technologies.
Table of contents
- Cover Page
- Title Page
- Copyright
- Foreword
- Preface
- Acknowledgments
- Contents
- Introduction
-
Part One: CLASSICAL MARKET PREDICTION
-
1: Classical Intermarket Analysis as a Predictive Tool
- WHAT IS INTERMARKET ANALYSIS?
- USING INTERMARKET ANALYSIS TO DEVELOP FILTERS AND SYSTEMS
- USING INTERMARKET DIVERGENCE TO TRADE THE S&P500
- PREDICTING T-BONDS WITH INTERMARKET DIVERGENCE
- PREDICTING GOLD USING INTERMARKET ANALYSIS
- USING INTERMARKET DIVERGENCE TO PREDICT CRUDE
- PREDICTING THE YEN WITH T-BONDS
- USING INTERMARKET ANALYSIS ON STOCKS
-
2: Seasonal Trading
- TYPES OF FUNDAMENTAL FORCES
- CALCULATING SEASONAL EFFECTS
- MEASURING SEASONAL FORCES
- THE RUGGIERO/BARNA SEASONAL INDEX
- STATIC AND DYNAMIC SEASONAL TRADING
- JUDGING THE RELIABILITY OF A SEASONAL PATTERN
- COUNTERSEASONAL TRADING
- CONDITIONAL SEASONAL TRADING
- OTHER MEASUREMENTS FOR SEASONALITY
- BEST LONG AND SHORT DAYS OF WEEK IN MONTH
- TRADING DAY-OF-MONTH ANALYSIS
- DAY-OF-YEAR SEASONALITY
- USING SEASONALITY IN MECHANICAL TRADING SYSTEMS
- COUNTERSEASONAL TRADING
- 3: Long-Term Patterns and Market Timing for Interest Rates and Stocks
- 4: Trading Using Technical Analysis
- 5: The Commitment of Traders Report
-
1: Classical Intermarket Analysis as a Predictive Tool
- Part Two: STATISTICALLY BASED MARKET PREDICTION
- Part Three: MAKING SUBJECTIVE METHODS MECHANICAL
-
Part Four: TRADING SYSTEM DEVELOPMENT AND TESTING
-
15: Developing a Trading System
- STEPS FOR DEVELOPING A TRADING SYSTEM
- SELECTING A MARKET FOR TRADING
- DEVELOPING A PREMISE
- DEVELOPING DATA SETS
- SELECTING METHODS FOR DEVELOPING A TRADING SYSTEM
- DESIGNING ENTRIES
- DEVELOPING FILTERS FOR ENTRY RULES
- DESIGNING EXITS
- PARAMETER SELECTION AND OPTIMIZATION
- UNDERSTANDING THE SYSTEM TESTING AND DEVELOPMENT CYCLE
- DESIGNING AN ACTUAL SYSTEM
- 16: Testing, Evaluating, and Trading a Mechanical Trading System
-
15: Developing a Trading System
-
Part Five: USING ADVANCED TECHNOLOGIES TO DEVELOP TRADING STRATEGIES
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17: Data Preprocessing and Postprocessing
- DEVELOPING GOOD PREPROCESSING—AN OVERVIEW
- SELECTING A MODELING METHOD
- THE LIFE SPAN OF A MODEL
- DEVELOPING TARGET OUTPUT(S) FOR A NEURAL NETWORK
- SELECTING RAW INPUTS
- DEVELOPING DATA TRANSFORMS
- EVALUATING DATA TRANSFORMS
- DATA SAMPLING
- DEVELOPING DEVELOPMENT, TESTING, AND OUT-OF-SAMPLE SETS
- DATA POSTPROCESSING
- 18: Developing a Neural Network Based on Standard Rule-Based Systems
- 19: Machine Learning Methods for Developing Trading Strategies
- 20: Using Genetic Algorithms for Trading Applications
-
17: Data Preprocessing and Postprocessing
- References and Readings
- Index
Product information
- Title: Cybernetic Trading Strategies: Developing a Profitable Trading System with State-of-the-Art Technologies
- Author(s):
- Release date: June 1997
- Publisher(s): Wiley
- ISBN: 9780471149200
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