Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. To get the free app, enter your mobile phone number. 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.
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.
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:. 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. 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. Chan is also the author of Quantitative Trading: Find out more about him at www. Would you like to tell us about a lower price? If you are a seller for this product, would you like to suggest updates through seller support? Sponsored Products are advertisements for products sold by merchants on Amazon. When you click on a Sponsored Product ad, you will be taken to an Amazon detail page where you can learn more about the product and purchase it.
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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. 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. Whilst the title doesn't use the word quant, be assured the models are again from the quant school. 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. 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. 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. Was this review helpful to you? By Maurice Hamilton on November 9,More...