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<p>Acknowledgments vii</p> <p>Mission Statement viii</p> <p><b>PART I INTRODUCTION TO TRADING ALGORITHMS</b></p> <p>Preface to Part I 3</p> <p>1 History 7</p> <p>2 All About Trading Algorithms You Ever Wanted to Know . . . 9</p> <p>3 Algos Defined and Explained 11</p> <p>4 Who Uses and Provides Algos 13</p> <p>5 Why Have They Become Mainstream so Quickly? 17</p> <p>6 Currently Popular Algos 19</p> <p>7 A Perspective View From a Tier 1 Company 25</p> <p>8 How to Use Algos for Individual Traders 29</p> <p>9 How to Optimize Individual Trader Algos 33</p> <p>10 The Future – Where Do We Go from Here? 37</p> <p><b>PART II THE LESHIK-CRALLE TRADING METHODS</b></p> <p>Preface to Part II 41</p> <p>11 Our Nomenclature 49</p> <p>12 Math Toolkit 53</p> <p>13 Statistics Toolbox 61</p> <p>14 Data – Symbol, Date, Timestamp, Volume, Price 67</p> <p>15 Excel Mini Seminar 69</p> <p>16 Excel Charts: How to Read Them and How to Build Them 75</p> <p>17 Our Metrics – Algometrics 81</p> <p>18 Stock Personality Clusters 85</p> <p>19 Selecting a Cohort of Trading Stocks 89</p> <p>20 Stock Profiling 91</p> <p>21 Stylistic Properties of Equity Markets 93</p> <p>22 Volatility 97</p> <p>23 Returns – Theory 101</p> <p>24 Benchmarks and Performance Measures 103</p> <p>25 Our Trading Algorithms Described – The ALPHA ALGO Strategies 107</p> <p>1. ALPHA-1 (DIFF) 107</p> <p>1a. The ALPHA-1 Algo Expressed in Excel Function Language 109</p> <p>2. ALPHA-2 (EMA PLUS) V1 And V2 110</p> <p>3. ALPHA-3 (The Leshik-Cralle Oscillator) 112</p> <p>4. ALPHA-4 (High Frequency Real-Time Matrix) 112</p> <p>5. ALPHA-5 (Firedawn) 113</p> <p>6. ALPHA-6 (General Pawn) 113</p> <p>7. The LC Adaptive Capital Protection Stop 114</p> <p>26 Parameters and How to Set Them 115</p> <p>27 Technical Analysis (TA) 117</p> <p>28 Heuristics, AI, Artificial Neural Networks and Other Avenues to be Explored 125</p> <p>29 How We Design a Trading Alpha Algo 127</p> <p>30 From the Efficient Market Hypothesis to Prospect Theory 133</p> <p>31 The Road to Chaos (or Nonlinear Science) 139</p> <p>32 Complexity Economics 143</p> <p>33 Brokerages 147</p> <p>34 Order Management Platforms and Order Execution Systems 149</p> <p>35 Data Feed Vendors, Real-Time, Historical 151</p> <p>36 Connectivity 153</p> <p>37 Hardware Specification Examples 155</p> <p>38 Brief Philosophical Digression 157</p> <p>39 Information Sources 159</p> <p><b>APPENDICES</b></p> <p>Appendix A ‘The List’ of Algo Users and Providers 165</p> <p>Appendix B Our Industry Classification SECTOR Definitions 179</p> <p>Appendix C The Stock Watchlist 183</p> <p>Appendix D Stock Details Snapshot 185</p> <p>CD Files List 243</p> <p>Bibliography 245</p> <p>Index 249</p>

<b>Edward Leshik</b> has spent the last 12 years trading his own account and researching the microeconomics of the NASDAQ and New York Stock Exchange markets. Previously he was CEO of an electronics company, supplying point of sale electronics to major retailers such as Sears and Sunoco in Canada and Allied Breweries in the UK, where he gained considerable electronics experience and was the first to automate an assembly line using electronics in the UK. His main academic background is in mathematics and physics and he has a great interest in the theories of Universality and Complexity as applied to the markets. He is currently developing a fully automated algorithmic trading system with his co-author Jane Cralle. <p><b>Jane Cralle</b> began her career in stockbrokerage at PaineWebber, and later spent 22 years at Linker Capital Management Inc. managing the accounts of high net worth individuals. She has a wide knowledge of the markets and is an expert trader and investor - her extensive experience is invaluable gauging the ‘long run' of market evolution. She is currently researching and developing an automated algorithmic trading system with Edward, and her specialty of cluster analysis of the S&P index components is a work in progress background for a proposed book titled Stocks and their Personalities. Jane lives in Louisville with her husband, Rick Kremer, and three children, Sarah, Morgan and Jack.</p>

Algorithmic trading is becoming the industry lifeblood - it is cheaper, faster and easier to control than standard trading and it enables you to ‘pre-think' the market, executing complex math in real time. We are no longer limited by human ‘bandwidth', but the industry is secretive with few willing to share the secrets of their success.<br /> <br /> <p><i>An Introduction to Algorithmic Trading</i> is an introductory guide to this hugely popular area. It begins with demystifying this complex subject and providing readers with specific and usable algorithmic trading knowledge. It outlines the current trading algorithms, the basics of their design, what they are, how they work, how they are used, their strengths, their weaknesses, where the industry is now and where it is going.</p> <p>The book then features a section describing the choice of stocks to trade on the NASDAQ and the New York Stock Exchange, analytics, and metrics used to optimize trading results - and for the more adventurous reader, a section on how to design trading algorithms.</p> <p>Finally the authors demonstrate a selection of detailed proprietary and never before seen algorithms targeted exclusively for use by individual traders to trade their own accounts. These algorithms have been developed and used by the authors and are being published here for the very first time.</p> <p>This is an ideal book for the reader interested in understanding and harnessing the power of algorithmic trading systems, and is accompanied by a CD Rom which provides a quick ‘hands on' route to exploring the power of algorithmic trading on trade NASDAQ and NYSE stocks.</p>

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