Automation of Trading Machine for Traders (eBook)
XX, 130 Seiten
Springer Singapore (Verlag)
978-981-13-9945-9 (ISBN)
This Palgrave Pivot innovatively combines new methods and approaches to building dynamic trading systems to forecast future price direction in today's increasingly difficult and volatile financial markets. The primary purpose of this book is to provide a structured course for building robust algorithmic trading models that forecast future price direction.
Chan provides insider information and insights on trading strategies; her knowledge and experience has been gained over two decades as a trader in foreign exchange, stock and derivatives markets. She guides the reader to build, evaluate, and test the predictive ability and the profitability of abnormal returns of new hybrid forecasting models.
Jacinta Chan, PhD in Financial Statistics, is with the Faculty of Business and Accountancy at the University of Malaya, Malaysia. She shares her knowledge and skills gained over two decades as a forex dealer, equity research analyst, product development officer of the futures exchange and senior Vice President of the sales and dealing derivatives desk of a financial institution with her students in universities and trading courses all over the world.
This Palgrave Pivot innovatively combines new methods and approaches to building dynamic trading systems to forecast future price direction in today's increasingly difficult and volatile financial markets. The primary purpose of this book is to provide a structured course for building robust algorithmic trading models that forecast future price direction. Chan provides insider information and insights on trading strategies; her knowledge and experience has been gained over two decades as a trader in foreign exchange, stock and derivatives markets. She guides the reader to build, evaluate, and test the predictive ability and the profitability of abnormal returns of new hybrid forecasting models.
Preface 5
Acknowledgements 12
Contents 14
List of Figures 15
List of Tables 17
1 Introduction to Model Trading 19
Market Analysis 21
Technical Analysis 21
Fundamental Analysis 26
Algorithm Technical Trading Systems 27
Setup of a Model Trading Desk 30
Conclusion: Risk of Not Having an Algorithm Trading System 32
Review: The First Trading Lesson 34
References 35
2 Technical Indicators: Market Technicians Trading Tools 37
Introduction 37
Lagging Indicators 38
Simple Moving Average 38
Simple 20 Day Moving Average (MA20) 39
Optimized Simple Moving Average (OptMA) 40
3- and 21-Day Moving Averages Crossover (MAC 3,21) 42
Adjustable Moving Average? (AMA?) 44
Range Breakout Model 45
Fixed Percentage Price Envelope (Moving Average Envelope Band (SMA (1,20,1%))) 47
Standard Deviation Breakout Bands (BBZ) 48
Leading Indicators 51
Momentum 51
Conclusion: The Key to Model Trading Is the Inherent Technical Indicator 52
Review 52
References 54
3 Market Data Analysis 55
Introduction 55
Choosing the Markets to Trade 56
Descriptive Statistics 58
Conclusion: You Need a Positive Statistical Expectation Edge for Your Trading Strategy 59
Review 60
References 61
4 Development of Technical Algorithm Trading Systems 62
Introduction 62
Profile of an Algorithm Trend Trading System 63
Adjustable Moving Average? (AMA?) 67
Tests and Trading Results of Trading Rules 69
Abnormal Returns 71
Conclusion: AMA? Passes the In-Sample Profitable Tests and Needs to Be Assessed Further 73
Review 74
Appendix 75
Simple Moving Average Trading Rules 75
BBZ (Black Box Z-Test Statistics): BBZ Trading Rules 76
AMA? (Adjustable Moving Average?) 78
References 82
5 Development of Artificial Intelligence Algorithm Trading Systems 84
Introduction 84
Architecture of Artificial Intelligence Trading System 86
Nonlinear Autoregressive Neural Network with Exogenous Inputs (NARNNX) 86
N-CAMA? (One Hidden Layer, Ten Neutrons, 2 Delays ANN Model Using Closing Prices and AMA?) 88
Artificial Intelligence System N-CAMA’s Abnormal Returns 89
Conclusion 92
Review 92
Appendix 93
References 95
6 Test Results of the Profitability of New Trading Model 97
Introduction 97
Analysis of Trading Systems 98
Analyzing Test Results 98
View Results 99
Empirical Results and Discussion on Findings 100
Conclusion: N-CAMA? Needs a Stop to Proceed 103
Review 103
Reference 104
7 Evaluation and Stops 105
Introduction 105
Evaluation 106
Capital and Risk Management 111
Conclusion: Cutting Loss Is the Key to Survival in the Trading Game 113
Review 116
Appendix 118
References 120
8 Conclusion: End of Course and Beginning of Trading 121
Introduction 121
Summary Review of Trading Lessons 122
Trading Strategy of Trading Plan 123
Trading Checklist 124
Trading Plan 125
Check Your Trading Plan for the Market You Wish to Trade In 125
Do Your Own Research, Data Analysis and Testing, Innovation, and Stress Testing 125
Select the Most Suitable Technical Indicator for Your Market 126
Have a Risk Control Mechanism in Your Trading System 127
Calculate and Keep Excess for Your Capital Management 127
Keep a Trading Journal for Audit and Revision Purpose 127
Do Periodic Check and Revise from Step One 128
Lastly, Start Trading 128
Conclusion: Last Words—The Market Is Always Right 128
Review 129
Appendix 132
Glossary 134
Analysis 134
Chart Analysis 134
Technical Indicators 134
Trading Range Terms 136
Trading Trend Terms 136
Tests 136
Theories 137
Trading Terms 137
Bibliography 139
Index 142
Erscheint lt. Verlag | 2.12.2019 |
---|---|
Zusatzinfo | XX, 130 p. 11 illus., 10 illus. in color. |
Sprache | englisch |
Themenwelt | Recht / Steuern ► Wirtschaftsrecht |
Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung | |
Schlagworte | Adaptive Trading Rules • algorithmic trading • Algorithm Trading Model • Investments and Securities • Stock and Futures Markets • Technical Analysis |
ISBN-10 | 981-13-9945-X / 981139945X |
ISBN-13 | 978-981-13-9945-9 / 9789811399459 |
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