Customer Reviews

Algorithmic Trading and DMA: An introduction to direct access trading strategies

5 star:		(16)
4 star:		(6)
3 star:		(2)
2 star:		(0)
1 star:		(2)

 

 

Barry Johnson's book is a great introduction to electronic and algorithmic trading. The book is so well written that you will find yourself reading it like a novel. The contents are well chosen and the chapters are fairly balanced in terms of length and importance.

The approach used in the book is very pedagogic. The author illustrates each and every trading strategy with an example and a figure, which permits to clearly grasp the motivation, the intuition and the ideas behind each trading scenario. He takes a good time explaining the variables that determine prices, liquidity, market impact and volatility. He also provides a lot of references for the readers willing to go deeper on a specific topic, and the summaries at the end of each chapter are an excellent addition.

In my opinion it is far better to understand the mechanisms of trading in today's electronic environment than just learning ready-to-use recipes. It is indeed the ignorant use of financial instruments that is at the genesis of the current crisis. Therefore, the author has my full admiration and support because he manages to provide a full understanding and grounding of algorithmic trading.

However, I have to put only 4 stars for the following reasons.

Algorithmic trading is crucial today not only because it is far more reactive than human traders, but also because it can predict and exploit trading patterns more accurately. Unfortunately, the book only has a subsection on forecasting market conditions and short-term prediction of prices, trading volume and volatility. Each one of these topics deserves a full chapter because they are the main reason why we are switching from human trading to algorithmic trading.

Another topic that is crucial for algorithmic trading is arbitrage. Again, the book falls short, just adding a subsection on the topic. Moreover, the author cites a result that seems to show that implied volatility is a more accurate measure than statistical volatility such as GARCH. The empirical evidence says the contrary, i.e. that GARCH and other volatility measures like bipower variation predict better than implied volatility, in particular for high frequency data. This feature is in fact exploited by quantitative hedge funds and proprietary trading desks.

The author also skips the stylized facts from the empirical analysis of financial time series: returns are not normal and exhibit high peaks, fat tails, auto-correlation and volatility clustering. It is the evidence of these facts and the necessity to understand and control them that has given to Finance the mathematical and computational trend it currently has.

My suggestions for mathematical references are the following classic books:

A. Shiryaev Essentials of Stochastic Finance: Facts, Models, Theory
P. Embrechts Quantitative Risk Management: Concepts, Techniques, and Tools (Princeton Series in Finance)

Over the last fifteen years, algorithmic trading through direct market access has come to dominate market microstructure in equities and FX, and is important in other markets as well. In simpler words, if you trade, you need to understand algorithmic trading, either to use it or to stay out of its way. It's one major component of any quant trading strategy, and an important tool in any portfolio management application.

Of course, you don't have to understand internal combustion engines to drive a car. There are off-the-shelf products for algorithmic offered by dealers and standard toolkits sold by specialist providers. But if you want to open the hood, this is the right book. It's a straightforward engineer's guide to the technology, without extraneous economic theory or trading advice. It tells you how to build what you want, not what you should want or what the implications are of what other people want. This fills an important niche between market microstructure theory and descriptions of popular techniques. You need some theory AND some realistic, state-of-the-art practical examples to figure out this field. As far as I know, this is the only place to get both without a lot of nonsense, error and false mystery.

Even experienced practitioners will be impressed at how simple and logical this stuff is, when presented comprehensively and straightforwardly; and even seasoned theorists will see how things get a bit more complicated when the rubber meets the road. While the book is not organized historically, the actual evolution of ideas followed the logical development closely enough that you see how things developed from dealers with big orders trying to minimize market impact to controversial (mainly because they are also misunderstood) modern high-frequency trading techniques. The book brings you reasonably close to the cutting edge of practice, this book plus a few months experience at a top shop, plus some talent are all you need to set up your own black box. The field is changing rapidly, so that may not be true for long, but the basic grounding you get from this book will be valuable for years.

A good companion piece to this book, written in a similar spirit, is Inside the Black Box, which shows you what kind of quant strategies you might want to hook up to the kind of engine Barry Johnson tells you how to build.

I'm conscious that an early rave review raises suspicion that it comes from a friend of the author. For the sake of full disclosure, Barry Johnson sent me a link to a copy of the text prior to publication. But that's the full extent of my acquaintance with him.

Terminology time: when the average amateur thinks of "Algorithmic trading," he thinks of vast machine intelligences duking it out in microseconds using exotic signal processing techniques. Well, in the business, "algorithmic trading" generally refers to the process of finding liquidity for an instrument using a computer, generally done by a buy side trader. This may seem needlessly pedantic, but it's important, as this is an actual job description, and this is what the book is all about. It also relates to 2009's favorite whipping boy, "High Frequency Trading," and could be considered the premier book on this subject -it's the best one I've yet read anyway. In addition to describing the other end of a HF trade done intelligently, it describes how various arbitrageurs and other prop traders make their money (in ch 13 in particular). The appendices are also excellent, and there is a useful key to abbreviations and acronyms: something sorely missed in many other books.

The book is a model of clarity and trading didactics; I have read no better description of this sort of thing, anywhere. While I'm not qualified to say so, as I don't actually do such things for a living, I suspect it's extremely complete and accurate introduction to the subject. In addition to the didactics, it contains plenty of folk wisdom, practical advice, obscure information and good old horse sense.

In detail: For part I, ch 1 gives a basic overview of the subject, including necessary definitions (aka DMA versus algo trading versus ...). Ch 2 touches on market microstructure; this is excellent, both for the rank amateur, and the professional looking to be grounded in a clear exposition. Ch 3 a description of the different types of markets, asset classes, dark pools, dealer markets and etc. This is all basic stuff; the nuts and bolts of what we're talking about. On to part II; ch 4 gives a detailed description of the different order types one can use in different markets. Ch 5 gives the basic kinds of trading algorithms; VWAP, implementation shortfall and all that. Ch 6 is on the process of modeling transaction costs; this chapter doesn't give any algorithms for doing so; it is more of a framework for thinking about the problem from the point of view of the algorithmic trader. I originally thought ch 7 was one of the weaker chapters, though upon reflection it may be one of the most useful ones for assessing market behavior; I was focusing on the classical use of the word "optimal." Section III, chapter 8 order placement is a sort of review of market microstructure models of price formation, and a strategic break down of the way a trader thinks about the problem of order placement. That and the sections on dark liquidity: gold. Ch 9 is on tactics; also invaluable stuff. How does a trader fake out other traders, look for hidden liquidity, update the limit book to minimize signaling? Ch 10 can be seen as a collection of ways to use forecasting techniques in your trading algorithms. Lots of practical information mixed in here about "forecastibles" that everyone knows about (dividends, witching days, etc). It's not always obvious how to incorporate known future events into a trading strategy or algorithm: this chapter is very helpful. I'd have liked to see it done in some kind of Bayesian framework, but whatever; this is really practical, useful stuff. Ch 11, infrastructure; this goes over things like FIX (the protocol for talking to the broker), some graphs as to how the actual order process works, ideas on latency, testing, market compliance and so on. I'd have liked a little more information on things like tick databases, trading platforms and trade resolution infrastructure, but maybe such information would be out of date as soon as he wrote it. Anyway, mentioning the words and some problems with typical such software might be useful to the tyro. Part IV, Ch 12 is on portfolio trading. There is a decent introduction to classical portfolio theory, and some good ideas on minimizing portfolio risk using the author's "marginal contribution to risk" metric. I'd have liked some more information here, but perhaps this is an appropriate chapter for a book more or less on Algo trading and DMA, rather than prop trading. Ch 13 is on various multi-asset trading strategies; roughly speaking, forms of statistical arbitrage and prop trading. It's sort of an oddball chapter, as this isn't the primary subject matter of the book, but it's a topical subject, and I'm glad it's there. Ch 14 is on trading the news; also a very interesting topic, and subject of ongoing research. The author gives a lot of practical information here which could be useful to the experimenter. Chapter 15 on machine learning is probably the weakest of the book, though I can find no factual faults with it. It is a reasonable introduction to machine learning and data mining techniques. Personally, I'd have lost much of the stuff on ANN's, and added a bit on reinforcement learning, and perhaps a section on the block bootstrap (one of my favorite hobby horses) used for testing for overfitting. One idea I found really interesting was the notion of using artificial stock markets to test ideas. I've fiddled with these, though I never thought of using them to test ideas! That's a damn good idea. Honestly, I think most of the machine learning papers out there are crap, and their appearance in books like this are more or less smokescreens. Stuff like econometrics and particle filters: way more useful. Don't tell anyone I told you so. The 70 pages of appendices, well, they're all super helpful for figuring out how the actual markets work in detail. No doubt some of the details are already out of date, but the over all structure: priceless. A real map of world markets.

Don't know why he wrote it, but I'm glad he did. I'd have paid twice the cover price for the book. I've actually physically worn the thing out (it doesn't do well on beaches), and will probably order another copy.

This book won't tell you how to make money, but it'll give you the necessary background so you can understand what you need to do. It provides a solid, broad introduction to the basics of electronic trading today.

I've gone through most of the books on this area.. This is the only one I can recommend.

I am very grateful that this has been written. Recently there has been an enormous amount of ill-informed chatter about high frequency trading, dark pools and algorithmic trading. These are important topics. Indeed I would argue that no serious trader should be unaware of these concepts and their implications. Unfortunately, before now there had been no accessible introduction available.

This book has changed that. It is clearly written. It should be easily understood by anyone. It has plenty of examples. If there is any justice in the world this book will become a classic.

I sometimes buy two copies of good books so I can keep one at work and one at home, but in this case I will need two copies for work because one is certain to go "missing".

I am in the trading industry and have reviewed the efficacy of many types of trading strategies. This book should provide a good framework to help practioners understand what goes into algorithm construction and how certain decisions can lead to various outcomes. I wish it was a little more technical in some areas, spefically in transaction cost modeling, but overall it provides a good overview and is a useful tool for traders to understand how these systems work and how they can optimize their own trading decisions.

This is a general review of Quant trading techniques and technologies written by someone who, by his own admission, hails from the development side. It is quite comprehensive but don't expect any insights into trading strategies. Bits of (borrowed) wisdom are scattered around the book, especially, when it comes to predicting trading volume, cost allocation and cross-market relationships. It's a good read for someone who is starting out in the industry; for someone with significant experience it's mostly redundant.

This is an EXCELLENT text.

There is one caveat, and that is, for the type of person who needs in-depth coverage of this material, this book is a godsend. But if you're not one of those people - if you're looking for a more introductory text, then, yeah, you might not enjoy this book as much as I and other people have.

I suppose the best way to look at this book is that it kind of picks up where Larry Harris' "Trading & Exchanges" (also an excellent book by the way) ends. Mr. Johnson's book goes into even more nitty-gritty detail. I loved both the Harris text and this one.

A good book for someone either new to the field or an intermediate guy looking to fill some knowledge gaps. I'm a software guy in the trading industry and I thought it was good for my purposes. The topics are generally discussed at high levels to increase conceptual understandings without going into details on specifics. Not being a quant I found the more quanty topics informative while generally staying at a high level to allow me not get too bogged down in mathematical details.

This is simply a great introduction to trading. I have been on the (computer) programming side of the financial industry for around 10 years and found this book to be incredibly useful. I have recommended it to several of my colleagues and often see copies of this book on desks of programmers and quants.

Unfortunately I misplaced my copy recently, yet, despite the hefty price, I'll be ordering another one.