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March 2011 | ISBN: 0470689544 | 538| PDF | 1M
Interest in algorithmic trading is growing massively – it’s cheaper, faster and better to control than standard trading, it enables you to ‘pre-think’ the market, executing complex math in real time and take the required decisions based on the strategy defined. We are no longer limited by human ‘bandwidth’. The cost alone (estimated at 6 cents per share manual, 1 cent per share algorithmic) is a sufficient driver to power the growth of the industry. According to consultant firm, Aite Group LLC, high frequency trading firms alone account for 73% of all US equity trading volume, despite only representing approximately 2% of the total firms operating in the US markets. Algorithmic trading is becoming the industry lifeblood. But it is a secretive industry with few willing to share the secrets of their success.
The book begins with a step-by-step guide to algorithmic trading, demystifying this complex subject and providing readers with a specific and usable algorithmic trading knowledge. It provides background information leading to more advanced work by outlining the current trading algorithms, the basics of their design, what they are, how they work, how they are used, their strengths, their weaknesses, where we are now and where we are going.
The book then goes on to demonstrate a selection of detailed algorithms including their implementation in the markets. Using actual algorithms that have been used in live trading readers have access to real time trading functionality and can use the never before seen algorithms to trade their own accounts.
The markets are complex adaptive systems exhibiting unpredictable behaviour. As the markets evolve algorithmic designers need to be constantly aware of any changes that may impact their work, so for the more adventurous reader there is also a section on how to design trading algorithms.
All examples and algorithms are demonstrated in Excel on the accompanying CD ROM, including actual algorithmic examples which have been used in live trading.
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An_Introduction_to_Algorithmic_Trading__Basic_to_Advanced_Strategies__Wiley_Trading_.pdf
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Authors:
Edward Leshik 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.
Jane Cralle 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.
Contents:
Acknowledgments.
Mission Statement.PART I INTRODUCTION TO TRADING ALGORITHMS.
Preface to Part I.
1 History.
2 All About Trading Algorithms You Ever Wanted to Know . . ..
3 Algos Defined and Explained.
4 Who Uses and Provides Algos.
5 Why Have They Become Mainstream so Quickly?
6 Currently Popular Algos.
7 A Perspective View From a Tier 1 Company.
8 How to Use Algos for Individual Traders.
9 How to Optimize Individual Trader Algos.
10 The Future – Where Do We Go from Here?
PART II THE LESHIK-CRALLE TRADING METHODS.
Preface to Part II.
11 Our Nomenclature.
12 Math Toolkit.
13 Statistics Toolbox.
14 Data – Symbol, Date, Timestamp, Volume, Price.
15 Excel Mini Seminar.
16 Excel Charts: How to Read Them and How to Build Them.
17 Our Metrics – Algometrics.
18 Stock Personality Clusters.
19 Selecting a Cohort of Trading Stocks.
20 Stock Profiling.
21 Stylistic Properties of Equity Markets.
22 Volatility.
23 Returns – Theory.
24 Benchmarks and Performance Measures.
25 Our Trading Algorithms Described – The ALPHA ALGO Strategies.
1. ALPHA-1 (DIFF).
1a. The ALPHA-1 Algo Expressed in Excel Function Language.
2. ALPHA-2 (EMA PLUS) V1 And V2.
3. ALPHA-3 (The Leshik-Cralle Oscillator).
4. ALPHA-4 (High Frequency Real-Time Matrix).
5. ALPHA-5 (Firedawn).
6. ALPHA-6 (General Pawn).
7. The LC Adaptive Capital Protection Stop.
26 Parameters and How to Set Them.
27 Technical Analysis (TA).
28 Heuristics, AI, Artificial Neural Networks and Other Avenues to be Explored.
29 How We Design a Trading Alpha Algo.
30 From the Efficient Market Hypothesis to Prospect Theory.
31 The Road to Chaos (or Nonlinear Science).
32 Complexity Economics.
33 Brokerages.
34 Order Management Platforms and Order Execution Systems.
35 Data Feed Vendors, Real-Time, Historical.
36 Connectivity.
37 Hardware Specification Examples.
38 Brief Philosophical Digression.
39 Information Sources.
APPENDICES.
Appendix A ‘The List’ of Algo Users and Providers.
Appendix B Our Industry Classification SECTOR Definitions.
Appendix C The Stock Watchlist.
Appendix D Stock Details Snapshot.
CD Files List.
Bibliography.
Index.
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