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An Introduction to Algorithmic Trading is an introductory guide to this ...
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.
PART I INTRODUCTION TO TRADING ALGORITHMS.
Preface to Part I.
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.
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.
34 Order Management Platforms and Order Execution Systems.
35 Data Feed Vendors, Real-Time, Historical.
37 Hardware Specification Examples.
38 Brief Philosophical Digression.
39 Information Sources.
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.