Preface xv

Chapter 1 Introduction 1

The Expanding Role of Technical Analysis 1

Convergence of Trading Styles in Stocks and Futures 3

Professional and Amateur 5

Random Walk 6

Deciding on a Trading Style 7

Measuring Noise 9

Maturing Markets and Globalization 12

Background Material 14

System Development Guidelines 15

Objectives of This Book 16

Profile of a Trading System 17

A Word about the Notation Used in This Book 20

A Final Comment 20

Chapter 2 Basic Concepts and Calculations 21

A Brief Word About Data 22

Simple Measures of Error 23

On Average 24

Price Distribution 28

Moments of the Distribution: Mean, Variance, Skewness, and Kurtosis 32

Choosing Between Frequency Distribution and Standard Deviation 37

Measuring Similarity 38

Standardizing Risk and Return 40

The Index 45

An Overview of Probability 50

Supply and Demand 56

Chapter 3 Charting 67

Finding Consistent Patterns 68

What Causes the Major Price Moves and Trends? 70

The Bar Chart and Its Interpretation by Charles Dow 71

Chart Formations 80

Trendlines 81

One-Day Patterns 89

Continuation Patterns 101

Basic Concepts in Chart Trading 105

Accumulation and Distribution: Bottoms and Tops 106

Episodic Patterns 118

Price Objectives for Bar Charting 119

Implied Strategies in Candlestick Charts 126

Practical Use of the Bar Chart 131

Evolution in Price Patterns 134

Chapter 4 Charting Systems 137

Dunnigan and the Thrust Method 138

Nofri’s Congestion-Phase System 141

Outside Days and Inside Days 143

Pivot Points 145

Action and Reaction 146

Programming the Channel Breakout 153

Moving Channels 155

Commodity Channel Index 156

Wyckoff’s Combined Techniques 157

Complex Patterns 158

Computer Recognition of Chart Patterns 160

Chapter 5 Event-Driven Trends 167

Swing Trading 167

Point-and-Figure Charting 176

The N-Day Breakout 195

Chapter 6 Regression Analysis 207

Components of a Time Series 207

Characteristics of the Price Data 208

Linear Regression 210

Linear Correlation 218

Nonlinear Approximations for Two Variables 222

Transforming Nonlinear to Linear 225

Multivariate Approximations 228

ARIMA 233

Basic Trading Signals Using a Linear Regression Model 238

Measuring Market Strength 241

Chapter 7 Time-Based Trend Calculations 243

Forecasting and Following 244

Price Change over Time 247

The Moving Average 248

The Moving Median 255

Geometric Moving Average 255

Accumulative Average 256

Drop-off Effect 256

Exponential Smoothing 257

Plotting Lags and Leads 267

Chapter 8 Trend Systems 269

Why Trend Systems Work 269

Basic Buy and Sell Signals 274

Bands and Channels 280

Choosing the Calculation Period for the Trend 290

A Few Classic Single-Trend Systems 291

Comparison of Single-Trend Systems 295

Techniques Using Two Trendlines 307

Three Trends 314

Comprehensive Studies 318

Selecting the Trend Speed to Fit the Problem 318

Moving Average Sequences: Signal Progression 319

Early Exits from a Trend 322

Projecting Moving Average Crossovers 323

Early Identification of a Trend Change 323

Chapter 9 Momentum and Oscillators 325

Momentum 326

Adding Volume to Momentum 339

Divergence Index 342

Visualizing Momentum 343

Oscillators 345

Double-Smoothed Momentum 364

Velocity and Acceleration 369

Hybrid Momentum Techniques 375

Momentum Divergence 377

Some Final Comments on Momentum 385

Chapter 10 Seasonality and Calendar Patterns 387

Seasonality Never Disappears 388

The Seasonal Pattern 389

Popular Methods for Calculating Seasonality 390

Classic Methods for Finding Seasonality 408

Weather Sensitivity 420

Identifying Seasonal Trades 422

Seasonality and the Stock Market 439

Common Sense and Seasonality 449

Chapter 11 Cycle Analysis 451

Cycle Basics 451

Uncovering the Cycle 465

Maximum Entropy 481

Short Cycle Indicator 489

Phasing 491

Chapter 12 Volume, Open Interest, and Breadth 495

Futures Volume and Open Interest 496

Extended Hours and 24-Hour Trading 497

Variations from the Normal Patterns 498

Standard Interpretation 502

Volume Indicators 506

Breadth Indicators 518

Is One Volume or Breadth Indicator Better than Another? 524

More Trading Methods Using Volume and Breadth 525

An Integrated Probability Model 533

Intraday Volume Patterns 534

Filtering Low Volume 537

Market Facilitation Index 538

Chapter 13 Spreads and Arbitrage 541

Dynamics of Futures Intramarket Spreads 542

Carrying Charges 543

Spreads in Stocks 546

Spread and Arbitrage Relationships 547

Risk Reduction in Spreads 548

Arbitrage 549

The Carry Trade 580

Implied Versus Historic Volatility 584

Changing Spread Relationships 589

Intermarket Spreads 591

Chapter 14 Behavioral Techniques 607

Measuring the News 608

Event Trading 614

Commitment of Traders Report 627

Opinion and Contrary Opinion 635

Fibonacci and Human Behavior 642

Elliott’s Wave Principle 646

Price Target Constructions Using the Fibonacci Ratio 656

Fischer’s Golden Section Compass System 657

W. D. Gann: Time and Space 662

Financial Astrology 668

Chapter 15 Short-Term Patterns 683

Projecting Daily Highs and Lows 684

Time of Day 686

Opening Gaps 699

Weekday, Weekend, and Reversal Patterns 707

Computer-Based Pattern Recognition 729

Artificial Intelligence Methods 732

Chapter 16 Day Trading 735

Impact of Transaction Costs 736

Slippage and Liquidity 738

Key Elements of Day Trading 741

Trading Using Price Patterns 748

Intraday Breakout Systems 752

High-Frequency Trading 769

Intraday Volume Patterns 773

Intraday Price Shocks 773

Chapter 17 Adaptive Techniques 777

Adaptive Trend Calculations 777

Adaptive Variations 787

Other Adaptive Momentum Calculations 792

Adaptive Intraday Breakout System 795

An Adaptive Process 797

Chapter 18 Price Distribution Systems 799

Accuracy is in the Data 799

Use of Price Distributions and Patterns to Anticipate Moves 803

The Importance of the Shape of the Distribution 808

A Purchaser’s Inventory Model 819

A Producer’s Selling Model 823

Steidlmayer’s Market Profile 824

A Fast Version of Market Profile 833

Chapter 19 Multiple Time Frames 835

Tuning Two Time Frames to Work Together 836

Displaying Two or Three Time Frames 837

Elder’s Triple Screen Trading System 838

Robert Krausz’s Multiple Time Frames 841

Martin Pring’s KST System 845

Chapter 20 Advanced Techniques 849

Measuring Volatility 849

The Price-Volatility Relationship 856

Using Volatility for Trading 860

Liquidity 869

Trends and Price Noise 871

Trends and Interest Rate Carry 874

Fuzzy Logic 874

Expert Systems 880

Game Theory 885

Fractals, Chaos, and Entropy 890

Genetic Algorithms 897

Neural Networks 905

Machine Learning and Artificial Intelligence 915

Replication of Hedge Funds 917

Chapter 21 System Testing 919

Expectations 920

Selecting the Test Data 921

Testing Integrity 927

Identifying the Parameters 929

Searching for the Best Result 931

Too Large to Test Everything 935

Visualizing and Interpreting Test Results 937

The Impact of Costs 950

Refining the Strategy Rules 951

Arriving at Valid Test Results 952

Comparing the Results of Two Trend Systems 959

Retesting to Stay Current 962

Profiting from the Worst Results 963

Testing Across a Wide Range of Markets 965

Price Shocks 970

Anatomy of an Optimization 972

Summarizing Robustness 976

Chapter 22 Adding Reality 983

Some Computer Basics 983

The Abuse of Power 988

Final Steps before Launch 989

Extreme Events 992

Gambling Techniques: The Theory of Runs 1000

Selective Trading 1008

System Trade-Offs 1008

Silver and Amazon: Too Good to Be True 1013

Similarity of Systematic Trading Signals 1014

Chapter 23 Risk Control 1021

Mistaking Luck for Skill 1021

Risk Aversion 1022

Liquidity 1027

Measuring Return and Risk 1028

Position Sizing 1041

Individual Trade Risk 1046

Kaufman on Stops and Profit-Taking 1050

Entering a Position 1053

Leverage 1058

Compounding a Position 1060

Selecting the Best Markets 1064

Probability of Success and Ruin 1072

Managing Equity Risk 1075

Ideal Leverage Using Optimal f 1078

Comparing Expected and Actual Results 1081

Chapter 24 Diversification and Portfolio Allocation 1089

Diversification 1090

Types of Portfolio Models 1095

Classic Portfolio Allocation Calculations 1097

Finding Optimal Portfolio Allocation Using Excel’s Solver 1100

Kaufman’s Genetic Algorithm Solution to Portfolio Allocation (GASP) 1103

Volatility Stabilization 1129

About the Companion Website 1134

Index 1135