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An Introduction to Algorithmic Trading. Basic to Advanced Strategies. Wiley Trading

  • ID: 1812296
  • Book
  • 272 Pages
  • John Wiley and Sons Ltd
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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.

An Introduction to Algorithmic Trading 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.

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.

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.

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.

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Acknowledgments vii

Mission Statement viii


Preface to Part I 3

1 History 7

2 All About Trading Algorithms You Ever Wanted to Know . . . 9

3 Algos Defined and Explained 11

4 Who Uses and Provides Algos 13

5 Why Have They Become Mainstream so Quickly? 17

6 Currently Popular Algos 19

7 A Perspective View From a Tier 1 Company 25

8 How to Use Algos for Individual Traders 29

9 How to Optimize Individual Trader Algos 33

10 The Future Where Do We Go from Here? 37


Preface to Part II 41

11 Our Nomenclature 49

12 Math Toolkit 53

13 Statistics Toolbox 61

14 Data Symbol, Date, Timestamp, Volume, Price 67

15 Excel Mini Seminar 69

16 Excel Charts: How to Read Them and How to Build Them 75

17 Our Metrics Algometrics 81

18 Stock Personality Clusters 85

19 Selecting a Cohort of Trading Stocks 89

20 Stock Profiling 91

21 Stylistic Properties of Equity Markets 93

22 Volatility 97

23 Returns Theory 101

24 Benchmarks and Performance Measures 103

25 Our Trading Algorithms Described The ALPHA ALGO Strategies 107

1. ALPHA–1 (DIFF) 107

1a. The ALPHA–1 Algo Expressed in Excel Function Language 109

2. ALPHA–2 (EMA PLUS) V1 And V2 110

3. ALPHA–3 (The Leshik–Cralle Oscillator) 112

4. ALPHA–4 (High Frequency Real–Time Matrix) 112

5. ALPHA–5 (Firedawn) 113

6. ALPHA–6 (General Pawn) 113

7. The LC Adaptive Capital Protection Stop 114

26 Parameters and How to Set Them 115

27 Technical Analysis (TA) 117

28 Heuristics, AI, Artificial Neural Networks and Other Avenues to be Explored 125

29 How We Design a Trading Alpha Algo 127

30 From the Efficient Market Hypothesis to Prospect Theory 133

31 The Road to Chaos (or Nonlinear Science) 139

32 Complexity Economics 143

33 Brokerages 147

34 Order Management Platforms and Order Execution Systems 149

35 Data Feed Vendors, Real–Time, Historical 151

36 Connectivity 153

37 Hardware Specification Examples 155

38 Brief Philosophical Digression 157

39 Information Sources 159


Appendix A The List of Algo Users and Providers 165

Appendix B Our Industry Classification SECTOR Definitions 179

Appendix C The Stock Watchlist 183

Appendix D Stock Details Snapshot 185

CD Files List 243

Bibliography 245

Index 249

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Edward Leshik
Jane Cralle
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