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Autore: ISBN: |
Jeffrey Owen Katz, Donna McCormick McGraw Hill 88243 380 Trading Operativo 2000 Inglese Listino: euro 72,50 0070580995 |
In quasi 400 pagine gli autori delineano tutte le componenti delle strategie di trading di successo, presentando modelli di ingresso, uscita e gestione della posizione in un'ottica completa e professionale. Ma non solo: questo testo insegna come verificare i risultati delle strategie anche su mercati differenziati e su svariate tipologie di portafoglio. Non manca una sezione che sviluppa ulteriormente le tecniche di uscita attingendo anche a tecniche di intelligenza artificiale.
Indice dei contenuti
PREFACE
INTRODUCTION
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
PART I: Tools of the Trade Introduction
CHAPTER 1 DATA
Types of Data - Data Time Frames Data Quality Data Sources and Vendors
CHAPTER 2 SIMULATORS
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
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?
CHAPTER 4 STATISTICS
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
PART II: The Study of Entries
Introduction
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
Kinds of Breakouts - Characteristics of Breakouts - Testing Breakout Models Channel Breakout Entries (close only channel breakouts; highest high/owest 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
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?
CHAPTER 7 OSCILLATOR-BASED ENTRIES
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
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
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
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
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 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
What Are Genetic Algorithms? - Evolving Rule-Based Entry Models - Evolving an Entry Model (the rule templates) Test Methodology (code fo revolving 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?
PART III: The-Study of Exits
Introduction
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
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
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?
CHAPTER 15 ADDING ARTIFICIAL INTELLIGENCE TO EXITS
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
The Big Picture - Points of Light - Looking into the Light Notice
Companion Software Available Appendix
References and Suggested Reading