Building winning algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading
著者
書誌事項
Building winning algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading
（Wiley trading series）
Wiley, c2014
- : pbk
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注記
Includes index
内容説明・目次
内容説明
Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas.
A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system-enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm.
Learn the systems that generated triple-digit returns in the World Cup Trading Championship
Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms
Test your new system using historical and current market data
Mine market data for statistical tendencies that may form the basis of a new system
Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.
目次
Acknowledgments ix
About the Author x
Introduction 1
Part I A Trader's Journey 7
Chapter 1 The Birth of a Trader 9
Chapter 2 Enough Is Enough 15
Chapter 3 World Cup Championship of Futures Trading (R) Triumph 23
Chapter 4 Making the Leap-Transitioning to Full Time 33
Part II Your Trading System 41
Chapter 5 Testing and Evaluating a Trading System 43
Chapter 6 Preliminary Analysis 53
Chapter 7 Detailed Analysis 61
Chapter 8 Designing and Developing Systems 71
Part III Developing a Strategy 77
Chapter 9 Strategy Development-Goals and Objectives 79
Chapter 10 Trading Idea 83
Chapter 11 Let's Talk about Data 93
Chapter 12 Limited Testing 103
Chapter 13 In-Depth Testing/Walk-Forward Analysis 115
Chapter 14 Monte Carlo Analysis and Incubation 129
Chapter 15 Diversification 133
Chapter 16 Position Sizing and Money Management 139
Chapter 17 Documenting the Process 147
Part IV Creating a System 153
Chapter 18 Goals, Initial and Walk-Forward Testing 155
Chapter 19 Monte Carlo Testing and Incubation 163
Part V Considerations Before Going Live 175
Chapter 20 Account and Position Sizing 177
Chapter 21 Trading Psychology 187
Chapter 22 Other Considerations before Going Live 195
Part VI Monitoring a Live Strategy 203
Chapter 23 The Ins and Outs of Monitoring a Live Strategy 205
Chapter 24 Real Time 219
Part VII Cautionary Tales 233
Chapter 25 Delusions of Grandeur 235
Conclusion 243
Appendix A Monkey Trading Example, TradeStation Easy Language Code 247
Appendix B Euro Night Strategy, TradeStation Easy Language Format 255
Appendix C Euro Day Strategy, TradeStation Easy Language Format 259
About the Companion Web Site 263
Index 265
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