Details

Quantitative Trading


Quantitative Trading

How to Build Your Own Algorithmic Trading Business
Wiley Trading 2. Aufl.

von: Ernest P. Chan

32,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 28.06.2021
ISBN/EAN: 9781119800088
Sprache: englisch
Anzahl Seiten: 256

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

<p><b>Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field</b></p> <p>In the newly revised Second Edition of <i>Quantitative Trading: How to Build Your Own Algorithmic Trading Business</i>, quant trading expert Dr. Ernest P. Chan shows you how to apply both time-tested and novel quantitative trading strategies to develop or improve your own trading firm.</p> <p>You'll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as:</p> <ul> <li>Updated back tests on a variety of trading strategies, with included Python and R code examples</li> <li>A new technique on optimizing parameters with changing market regimes using machine learning.</li> <li>A guide to selecting the best traders and advisors to manage your money</li> </ul> <p>Perfect for independent retail traders seeking to start their own quantitative trading business, or investors looking to invest in such traders, this new edition of <i>Quantitative Trading</i> will also earn a place in the libraries of individual investors interested in exploring a career at a major financial institution.</p>
<p>Preface to the 2nd Edition xi</p> <p>Preface xv</p> <p>Acknowledgments xxi</p> <p><b>Chapter 1: The Whats, Whos, and Whys of Quantitative Trading 1</b></p> <p>Who Can Become a Quantitative Trader? 2</p> <p>The Business Case for Quantitative Trading 4</p> <p>Scalability 5</p> <p>Demand on Time 5</p> <p>The Nonnecessity of Marketing 7</p> <p>The Way Forward 8</p> <p><b>Chapter 2: Fishing for Ideas 11</b></p> <p>How to Identify a Strategy that Suits You 14</p> <p>Your Working Hours 14</p> <p>Your Programming Skills 15</p> <p>Your Trading Capital 15</p> <p>Your Goal 19</p> <p>A Taste for Plausible Strategies and Their Pitfalls 20</p> <p>How Does It Compare with a Benchmark, and How Consistent Are Its Returns? 20</p> <p>How Deep and Long is the Drawdown? 23</p> <p>How Will Transaction Costs Affect the Strategy? 24</p> <p>Does the Data Suffer from Survivorship Bias? 26</p> <p>How Did the Performance of the Strategy Change over the Years? 27</p> <p>Does the Strategy Suffer from Data-Snooping Bias? 28</p> <p>Does the Strategy “Fly under the Radar” of Institutional Money Managers? 30</p> <p>Summary 30</p> <p>References 31</p> <p><b>Chapter 3: Backtesting 33</b></p> <p>Common Backtesting Platforms 34</p> <p>Excel 34</p> <p>MATLAB 34</p> <p>Python 36</p> <p>R 38</p> <p>QuantConnect 40</p> <p>Blueshift 40</p> <p>Finding and Using Historical Databases 40</p> <p>Are the Data Split and Dividend Adjusted? 41</p> <p>Are the Data Survivorship-Bias Free? 44</p> <p>Does Your Strategy Use High and Low Data? 46</p> <p>Performance Measurement 47</p> <p>Common Backtesting Pitfalls to Avoid 57</p> <p>Look-Ahead Bias 58</p> <p>Data-Snooping Bias 59</p> <p>Transaction Costs 72</p> <p>Strategy Refinement 77</p> <p>Summary 78</p> <p>References 79</p> <p><b>Chapter 4: Setting Up Your Business 81</b></p> <p>Business Structure: Retail or Proprietary? 81</p> <p>Choosing a Brokerage or Proprietary Trading Firm 85</p> <p>Physical Infrastructure 87</p> <p>Summary 89</p> <p>References 91</p> <p><b>Chapter 5: Execution Systems 93</b></p> <p>What an Automated Trading System Can Do for You 93</p> <p>Building a Semiautomated Trading System 95</p> <p>Building a Fully Automated Trading System 98</p> <p>Minimizing Transaction Costs 101</p> <p>Testing Your System by Paper Trading 103</p> <p>Why Does Actual Performance Diverge from Expectations? 104</p> <p>Summary 107</p> <p><b>Chapter 6: Money and Risk Management 109</b></p> <p>Optimal Capital Allocation and Leverage 109</p> <p>Risk Management 120</p> <p>Model Risk 124</p> <p>Software Risk 125</p> <p>Natural Disaster Risk 125</p> <p>Psychological Preparedness 125</p> <p>Summary 130</p> <p>Appendix: A Simple Derivation of the Kelly Formula when Return Distribution is Gaussian 131</p> <p>References 132</p> <p><b>Chapter 7: Special Topics in Quantitative Trading 133</b></p> <p>Mean-Reverting versus Momentum Strategies 134</p> <p>Regime Change and Conditional Parameter Optimization 137</p> <p>Stationarity and Cointegration 147</p> <p>Factor Models 160</p> <p>What is Your Exit Strategy? 169</p> <p>Seasonal Trading Strategies 174</p> <p>High-Frequency Trading Strategies 186</p> <p>Is it Better to Have a High-Leverage versus a High-Beta Portfolio? 188</p> <p>Summary 190</p> <p>References 192</p> <p><b>Chapter 8: Conclusion 193</b></p> <p>Next Steps 197</p> <p>References 198</p> <p>Appendix: A Quick Survey of MATLAB 199</p> <p>Bibliography 205</p> <p>About the Author 209</p> <p>Index 211</p>
<p><b>ERNEST P. CHAN, P<small>H</small>D,</b> is an expert in the application of statistical models and software for trading currencies, futures, and stocks. He holds a doctorate in theoretical physics from Cornell University and is Managing Member of investment management firm QTS Capital Management and founder of financial machine learning firm Predictnow.ai.</p>
<p> Algorithmic trading, also known as statistical or quantitative trading, is widely used by pension funds and other institutional investors to maximize returns and minimize risks. But it has traditionally been out of reach for independent, do-it-yourself investors. </p><p>In the newly revised <i>Second Edition</i> of <i>Quantitative Trading: How to Build Your Own Algorithmic Trading Business</i>, statistical trading expert Dr. Ernest P. Chan delivers a step-by-step guide to getting started with quantitative trading. Ideal for independent traders who hope to challenge powerful industry professionals at their own game, or a person who aspires to work as a quantitative trader at a major financial institution, the book walks you through the ins and outs of statistical trading. </p><p> The author offers an interactive guide showing readers how to develop their own spreadsheet tools in Excel, Matlab, Python, R, and tutorials on how to develop their own homegrown proprietary trading operations. He also provides downloadable spreadsheets that supplement the material contained in the book. </p> </p><p><i>Quantitative Trading</i> contains updated tests on trading strategies, adding Python and R codes, and a new parameter optimization method using machine learning. </p><p> Perfect for current and aspiring quantitative investors and traders, this new edition of <i>Quantitative Trading</i> will also earn a place in the libraries of institutional and individual investors who seek an authoritative and practical source of information on one of the most popular trading strategies in the world today.</p>
<p><b>PRAISE FOR</p><p><i>Quantitative</i> Trading 2ND EDITION</b></p><p>“Ernie’s timely update to his classic <i>Quantitative Trading</i> is extraordinary in that, despite the modernization of the content, all the fundamentals remain unchanged and have clearly stood the test of time since the first edition. If you want to be a competitive swimmer, you need to learn the fundamentals of swimming first. Trading is no different; Ernie makes the fundamentals as simple as possible, but no simpler (as Einstein would say) and strikes the perfect balance between intuition and technical depth. Those specifically interested in trading, and anyone generally interested in understanding how modern financial markets work, will benefit from reading the <i>Second Edition of Quantitative Trading</i>." <BR><b>—CRAIG BETTS,</b> mathematician and Founder, Solace </p><p>“As technology has evolved, so has the ease in developing trading strategies. Ernest Chan does all traders, current and prospective, a real service by succinctly outlining the tremendous benefits, but also some of the pitfalls, in utilizing many of the recently implemented quantitative trading techniques."<BR><b>—PETER BORISH,</b> Chairman and CEO, Computer Trading Corporation; Founding Partner, Tudor Investment Corporation </p><p>“Out of the many books and articles on quantitative trading that I've read over the years, very few have been of much use at all. In most instances, the authors have no real knowledge of the subject matter or do have something important to say but are unwilling to do so because of fears of having trade secrets stolen. Ernie subscribes to a different credo: Share meaningful information and have meaningful interactions with the quantitative community at large. Ernie successfully distills a large amount of detailed and difficult subject matter down to a very clear and comprehensive resource for novice and pro alike."<BR><b>—STEVE HALPERN,</b> Founder, HCC Capital, LLC </p><p>“Often the hardest part of getting started is simply knowing what questions to ask. This holds especially true for fields like quantitative trading, which are shrouded in mystery and protected by impenetrable jargon. Readers of this book will not only learn the foundations of research and strategy development, but also gain pragmatic insight into the operational sides of the business. Ernie has written the ideal guide for those looking to go from zero-to-one in their quantitative trading journey."<BR><b>—COREY HOFFSTEIN,</b> Co-founder and CIO, Newfound Research </p>

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