An Introduction to Algorithmic Trading: Basic to Advanced Strategies 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.
The goal of this book is to:
- 1. Demystify algorithmic trading, provide some background on the state of the art, and explain who the major players are.
- 2. Provide brief descriptions of current algorithmic strategies and their user properties.
- 3. Provide some templates and tools for the individual trader to be able to learn a number of our proprietary strategies to take up-to date control over his trading, thus level the playing field and at the same time provide a flavor of algorithmic trading.
- 4. Outline the math and statistics we have used in the book while keeping the math content to a minimum.
- 5. Provide the requisite Excel information and explanations of formulas and functions to be able to handle the algorithms on the CD.
- 6. Provide the reader with an outline ‘grid’ of the algorithmic trading business so that further knowledge and experience can be ‘slotted’ into this grid.
- 7. Use a ‘first principles’ approach to the strategies for algorithmic trading to provide the necessary bedrock on which to build from basic to advanced strategies.
- 8. Describe the proprietary ALPHA ALGOS in Part II of the book to provide a solid foundation for later running of fully automated systems.
- 9. Make the book as self-contained as possible to improve convenience of use and reduce the time to get up and running.
- 10. Touch upon relevant disciplines which may be helpful in understanding the underlying principles involved in the strategy of designing and using trading algorithms.
- 11. Provide a detailed view of some of our Watchlist of stocks, with descriptions of each company’s operations. Provide a framework for analyzing each company’s trading characteristics using our proprietary metrics. It is our belief that an intimate knowledge of each stock that is traded provides a competitive advantage to the individual trader enabling a better choice and implementation of algo strategies.
- All About Trading Algorithms You Ever Wanted to Know . . .
- Algos Defined and Explained
- Who Uses and Provides Algos
- Why Have They Become Mainstream so Quickly?
- Currently Popular Algos
- A Perspective View From a Tier 1 Company
- How to Use Algos for Individual Traders
- How to Optimize Individual Trader Algos
- The Future – Where Do We Go from Here?
- Our Nomenclature
- Math Toolkit
- Statistics Toolbox
- Data – Symbol, Date, Timestamp, Volume, Price
- Excel Mini Seminar
- Excel Charts: How to Read Them and How to Build Them
- Our Metrics – Algometrics
- Stock Personality Clusters
- Selecting a Cohort of Trading Stocks
- Stock Profiling
- Stylistic Properties of Equity Markets
- Returns – Theory
- Benchmarks and Performance Measures
- Our Trading Algorithms Described – The ALPHA ALGO Strategies
- Parameters and How to Set Them
- Technical Analysis (TA)
- Heuristics, AI, Artificial Neural Networks and Other Avenues to be Explored
- How We Design a Trading Alpha Algo
- From the Efficient Market Hypothesis to Prospect Theory
- The Road to Chaos (or Nonlinear Science)
- Complexity Economics
- Order Management Platforms and Order Execution Systems
- Data Feed Vendors, Real-Time, Historical
- Hardware Specification Examples
- Brief Philosophical Digression