Machine Trading: Deploying Computer Algorithms to Conquer the Markets (Wiley Trading) 1st Edition

Machine Trading had a ton of useful information for me. The first chapter looked at data sources for back-testing trading strategies. There was information about which are the best sites to get data from, which have good APIs, and the costs of these services. It was easy to see that the author had worked with lots of different types of data and vendors.The next few chapters look at analysis using MATLAB as the programming language. The code snippets are well described and fairly easy to understand or translate to another language.Another chapter which I enjoyed was the one on Artificial Intelligence. Actual techniques were shown in a simple manner and the techniques progressed from simple to more complicated. A good point was made how you want to try the simplest machine learning techniques first, before trying more advanced one. It was shown how neural networks generally do not perform that well on financial data. There was an example given showing that a neural network with only layer performed better than networks with too many layers.Later there is a detailed section about how orders work in the stock market, and how closing prices are often "consolidated". The consolidated closing (and opening) prices can cause trouble for back-testing strategies. Explanations were clear about potential pitfalls of using different types of market or limit orders.Another surprise was a chapter on bitcoin which had possible trading strategies on the crypto-currency. One of the advantages of bitcoin for analysis is that the order book is open and each trade specifies whether it was a buy or sell.The book wraps up with a discussion about maintaining a career in trading. I was impressed with the content, the explanations, and details that went into this book.

Ernest Chan writes with clarity and an experts perspective on algorithmic trading tools and techniques.

This book is 3rd in a series by author.I like the 1st book for its simplicity and easy to follow.2nd is a little more advanced and formal but still easy to follow.This one is most advanced, and a little difficult to follow.If you liked previous books, this one is also worth a reading as a guide into advanced techniques.

No good if you barely know what you're doing. Great guidelines, but hard to follow if you've got only a bit of experience, great idea generation if you do know what you're doing, but light on critical details and rigour, and finally next to useless if you're advanced/practitioner, because you wouldn't be worth your salt if you didn't know these things already. That said, all in all a good read if it isn't your only one.

Great entry level book for quantitative trading. Targets primarily individual (retail) hobby-traders who have some basic understanding of statistics and programming. What I particularly like is that this material doesn't give ready made strategies, but teaches a methodology how to develop one.

The author gives wise ideas on machine trading. However, it is super useless if you are learning machine learning/trading or you are performing a mathematical program in trading. Definitely not recommend it.

this is a good book if you do your homework. People here giving bad reviews think the author will give his full blown strategies for free - nobody does that.As with any book in this subject, it adds up to your knowledge but you still need to do the hard work.It does lack some depth though and I wish he could give some more information on cryptocurrencies - this chapter is pretty vague.Overall a good book.

High programming familiarity would be a plus, great and advanced concepts discussed in the book which will open your mind to other subjects such as trading AI and learning more complex programming tasks