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Algorithmic Trading: Winning Strategies and Their Rationale, by Ernie Chan
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Praise for Algorithmic Trading
"Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers."
—DAREN SMITH, CFA, CAIA, FSA, Managing Director, Manager Selection & Portfolio Construction, University of Toronto Asset Management
"Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses."
—Roger Hunter, Mathematician and Algorithmic Trader
- Sales Rank: #104441 in Books
- Published on: 2013-05-28
- Original language: English
- Number of items: 1
- Dimensions: 9.10" h x .80" w x 6.00" l, .85 pounds
- Binding: Hardcover
- 224 pages
From the Inside Flap
In his well-received first book Quantitative Trading, Dr. Ernest Chan addressed the essential techniques an algorithmic trader needs to succeed at this demanding endeavor. While some useful example strategies were presented throughout, they were not the main focus of the book.
With this in mind, Dr. Chan has created a practical guide to algorithmic trading strategies that can be readily implemented by both retail and institutional traders alike. More than an academic treatise on financial theory, Algorithmic Trading is an accessible resource that blends some of the most useful financial research done in the last few decades with valuable insights Dr. Chan has gained from actually exploiting some of those theories in live trading.
Engaging and informative, Algorithmic Trading skillfully covers a wide array of strategies. Broadly divided into the mean-reverting and momentum camps, it lays out standard techniques for trading each category of strategies and, equally important, the fundamental reasons why a strategy should work. The emphasis throughout is on simple and linear strategies, as an antidote to the over-fitting and data-snooping biases that often plague complex strategies. Along the way, it provides comprehensive coverage of:
- Choosing the right automated execution platform as well as a backtesting platform that will allow you to reduce or eliminate common pitfalls associated with algorithmic trading strategies
- Multiple statistical techniques for detecting "time series" mean reversion or stationarity, and for detecting cointegration of a portfolio of instruments
- Simple techniques for trading mean-reverting portfolios—linear, Bollinger band, and Kalman filter—and whether using raw prices, log prices, or ratios make the most sense as inputs to these tests and strategies
- Mean-reverting strategies for stocks, ETFs, currencies, and futures calendar and intermarket spreads
- The four main drivers of momentum in stocks and futures, and strategies that can extract time series and cross sectional momentum
- Newer momentum strategies based on news events and sentiment, leveraged ETFs, order flow, and high-frequency trading
- Issues involving risk and money management based on the Kelly formula, but tempered with the author's practical experience in risk management involving black swans, Constant Proportion Portfolio Insurance, and stop losses
Mathematics and software are the twin languages of algorithmic trading. This book stays true to that view by using a level of mathematics that allows for a more precise discussion of the concepts involved in financial markets. And it includes illustrative examples that are built around MATLAB© codes, which are available for download.
While Algorithmic Trading contains an abundance of strategies that will be attractive to both independent and institutional traders, it is not a step-by-step guide to implementing them. It offers a realistic assessment of common algorithmic trading techniques and can help serious traders further refine their skills in this field.
About the Author
ERNEST P. CHAN is the Managing Member of QTS Capital Management, LLC. He has worked for various investment banks (Morgan Stanley, Credit Suisse, Maple) and hedge funds (Mapleridge, Millennium Partners, MANE) since 1997. Chan received his PhD in physics from Cornell University and was a member of IBM's Human Language Technologies group before joining the financial industry. He was a cofounder and principal of EXP Capital Management, LLC, a Chicago-based investment firm. Chan is also the author of Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley) and a popular financial blogger at http://epchan.blogspot.com. Find out more about him at www.epchan.com.
Most helpful customer reviews
81 of 81 people found the following review helpful.
A good primer for the quant newbie
By ETO Trader
So nearly four and half years after writing the first review of Dr Chan's first book I am back again writing the first review for his second.
Things to note:
1. All the examples in the book are again in MATLAB, so if you don't have MATLAB you will be at a disadvantage.
2. Whilst the title of the book includes the phrase Algorithmic Trading. It, like the first book, doesn't actually show you how to connect a MATLAB model or system to the market so it can run as an algorithmic trading platform. This was a criticism of the first book. However, if you Google "MATLAB as an Automated Execution System" you'll find a paper that Dr Chan wrote that shows you how to connect MATLAB to Interactive Brokers via a third party MATLAB interface.
3. Whilst the title doesn't use the word quant, be assured the models are again from the quant school. Readers from the TA school of school of oscillators, Gann, MACD etc are not catered for.
Now the book itself:
In the introduction Dr Chan makes it clear the book contains prototype strategies. The book isn't a collection of "strategy recipes" (his term) rather it's about why some strategies should work and how we can look to test and refine them. For each presented strategy we are given a model using MATLAB code. The code is only a snippet; you need to go to Dr Chan's website for the full code.
Many of the models will need further work to accommodate the reader's circumstances, but Dr Chan is clear that he isn't presenting complete models. The book is essentially about why certain approaches to the market should work in theory given the "maths" and what we know about market operations.
Many of the discussed strategies will be familiar to readers of Dr Chan's blog and his first book. The main division in the book is between mean reversion and momentum strategies, with mean reversion getting the greatest attention.
Dr Chan highlights the challenges facing traders of mean reversion, particularly those focusing on pure stock pairs, his preference now is more towards ETFs.
As you come to expect from Dr Chan his theories are well supported by maths and any reader will get a good primer on stationarity, cointegration, dickey fuller test and the Hurst Exponent.
My Summary:
I devoured the first book and spent many hours coding and testing the ideas that were presented. This time around I felt there isn't much new content for a reader or practitioner with a reasonable interest in pair trading, basket trading or a quant approach to momentum trading.
If you haven't read the first book, then this is a better book. It has been updated to reflect the market conditions of the last few years, plus there are greater descriptions of the theory behind why some of these quant models work and ways in which we should look to improve them. So in effect it is an ideal primer for the quant newbie.
As a standalone book and with the knowledge the ideal reader is quant focused then the book is a four.
Readers who already have the first book and maintain an interest in quant will probably feel a little short changed this time around.
3 of 3 people found the following review helpful.
An alternate title: How to Create Winning Strategies and Their Rationale
By Seasoned Greetings
Makes you think about what you are really trying to do. Relatively technical, calculus is a good thing to understand. It does not try and sell you trading strategies or systems, but methods and the underlying discipline to achieve good strategies. I like this book. E. Chan is honest, open, and understandable. the book does not hold your hand but points in the right direction. If you are trying to design a system, this offers many good mean to do so.
4 of 4 people found the following review helpful.
Worth reading but needs to be supplemented with other books
By Aussie C
Good trading ideas, explained clearly and with good mathematical justification. It's a short book though, and important topics like risk management are not really covered in depth.
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