Inside the Black Box: A Simple Guide to Quantitative and High-Frequency Trading

by Rishi K. Narang

New edition of book that demystifies quant and algo trading In this updated edition of his bestselling book, Rishi K Narang offers in a straightforward, nontechnical style―supplemented by real-world examples and informative anecdotes―a reliable resource takes you on a detailed tour through the black box. He skillfully sheds light upon the work that quants do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. This new edition includes information on High Frequency Trading. This new edition of Inside the Black Box explains quant investing without the jargon and goes a long way toward educating investment professionals.

Genres: Finance, Business, Academic

336 pages, Hardcover

First published August 4, 2009

Reviews

[Kevin · Rating 4 out of 5]

Overall, I thought this book had some great insight into quantitative trading, but I wasn’t as impressed by the short section at the end regarding high-frequency trading. Rishi Narang has nearly 20 years of experience with quantitative trading and hedge funds, and shares his insight and perspectives into a number of different aspects of the subject. He breaks down the different parts of the “black box,” that is, the components that go into quantitative trading. He summarizes the black box in a diagram on page 19 where the Portfolio Construction Model is a function of the Alpha Model, Risk Model, and Transaction Cost Model. This has a feedback loop with the Execution Model. All of these are improved by research, and fed by data. He then goes through the different components. Alpha Models can be either theory-driven or data-driven. “Most of what theory-driven quants do can be relatively easily fit into one of six classes of phenomena: trend, reversion, technical sentiment, value/yield, growth, and quality. It is worth noting that the kinds of strategies that quants utilize are actually exactly the same as those that can be utilized by discretionary traders seeking alpha.” (26)
He then talks about limiting risk. The primary differences in the ways this is done is: “The manner in which size is limited, How risk is measured, What is having its size limited.” (69)
Next, he talks about the Transaction cost models. These help balance the benefits of making a trade with the associated costs. Costs discussed include commissions and fees, slippage (the price you pay changes before you can make a trade), and market impact. He then goes into linear, piecewise linear, and quadratic cost models, finding that piecewise linear seem to be a good balance between accuracy and computation time. (88)
Portfolio construction is discussed next. Different weightings and portfolio optimizers are discussed. (98)
Additionally, the importance of reliable, clean data is discussed, as well as continuing research to ensure that you are using good models and deprecating models whose effectiveness has decayed enormously over time.
Some risks unique to quant strategies were discussed, such as model misspecification or implementation errors, as well as regime change and crowded trades, which the model might not be as good at identifying.
He discussed some of the criticisms of quant trading, but mostly seemed to be creating straw men and knocking them down. He clearly likes quantitative trading, and might not be the best person to provide a balanced view. “Data mining is given a fairly bad name in financial circles. It is used interchangeably with another term that is actually deserving of such negative judgment: overfitting.” (210) I guess I don’t see why data mining is so terrible, but if people are instead thinking of overfitting, I can see why there is such hesitance to utilize it.
One of the best sections was on Evaluating Quants and Quant Strategies. This section provided much useful insight. He describes the two goals of the evaluator: “The first is to understand the strategy itself, including the kinds of risks it is taking and from what sources its returns are generated…The second goal in the evaluation of ta quant is to judge how good the practitioners themselves are.” (216) In order to get better information, he suggests reading the book The Interrogator by Raymond Toliver, saying that many of the general techniques of inquiry are useful in a manager interview as well. He lists 6 major components to an interview of a quant: “1. Research and strategy development 2. Data sourcing, gathering, cleaning, and management 3. Investment selection and structuring 4. Portfolio construction 5. Execution 6. Risk management and monitoring.” (219) He also breaks down the “edge” that a particular manager might have into 3 areas: “1. The investment process 2. A lack of competition 3. Something structural.” (223) I liked the quote provided on how a firm did very well: “To quote him loosely, ‘There is no secret sauce. We are constantly working to improve every area of our strategy. Our data is constantly being improved, our execution models are constantly being improved, our portfolio construction algorithms are constantly being improved…everything can always be better. We hire the right kinds of people and we give them an environment in which they can relentlessly work to improve everything we do, little by little.’” (232)
At the end of the book, he discussed high speed trading, where milliseconds matter, and high frequency trading, where many trades are made in the course of a day and they typically end the day with few or no ownership of any shares. This part was fine, but the discussion of potential drawbacks did not seem as balanced as it could have been. It did not end the book on a good note, as he seemed to be complaining about critics and saying that there isn’t a hint of anything wrong with HFT. My favorite quote was: “HFT isn’t evil any more than walking your dog is evil.” The book would probably be improved with the omission of that chapter.
With the exception of the questionable last section, I thought the book provided some great insight into the different components that make up a quantitative strategy, and different ways that a quantitative manager might approach them. I also really liked the steps he went through when evaluating quantitative managers, which is really pertinent to what the team I’m on does. Overall, this book had a lot of great content and insight that you can’t find many other places, because most people in his position don’t seem to write books like this. His familiarity and affinity make him a little biased when it comes to evaluating whether certain things are “good” or “bad,” but his unique perspective more than makes up for it.

[Josh Clausen · Rating 2 out of 5]

Although I’m sure many people would disagree, I found this book to have very little to offer that was mind-blowing. It could be the fact that I am in the financial field, but for a cover price of $49.95, one could expect a bit more

[Jessie · Rating 4 out of 5]

In general, I found the book really interesting. It was a great introduction to the different parts of the trading firm and how quantitative trading works in general. I would recommend this book to anyone starting a job in the trading space.

However, I was pretty unimpressed with the new section on HFT. Rather than discussing how HFT works, it mostly focuses on how HFT is really, really, really not evil, no I promise it’s fine. As someone who has worked in HFT and agrees HFT is generally good for markets, I was still quite disappointed with this section. While previous sections were mostly factual representations of how things worked, this felt section felt driven by emotion. “We Americans had to be told it was wrong to hold slaves … That doesn’t make farming or all farmers bad.“ When you start using slavery as comparison, you need to take a step back and try again.

[Jimmy · Rating 3 out of 5]

Narang gives a general, high-level overview on the various components of a typical quantitative hedge fund. Near the end, the book includes some brief discussions of high frequency trading as well as his defense of the practice despite the bad publicity typically associated with it.

This book is helpful for those who are new to alternative investments and offers little to experienced practitioners/investors as other reviews mentioned.

Lastly, the writing of this book is not the easiest to read, with many instances of logically disconnected paragraphs stuffed together as well as various repetitions of the same idea.

Overall, this book is an okay read as a "How It's Made" for quant funds in text format.

[Ayush · Rating 4 out of 5]

All the insights one could expect to learn about Quant, however the author in an effort to not sway from broader topic does not dive deep nonetheless develops great taxonomy and how everything fits together. The book does not need nor cover any quant math nor dissects any strategies in depth but it does shed light into each aspect of building quant systems. It also talks about HFT and debunks alot of myths and sour notions on the topic.

Overall, must read for anyone who doesn't work in the industry as a quant.

[Michelangelo Rubino · Rating 5 out of 5]

Provided that it's for people with intermediate knowledge of this topic or less, provided that there are no trading strategies and no heavy formulas, this book describes how each part of a quant trading system really works: alphas, risk management, transaction costs... Parts 1 and 2 are an introduction to the black box, while parts 3 and 4 are more focused on HST/HFT and on criticism about quantitative trading. A book recommended to people who want to know more about this field

[Andrew Chen · Rating 4 out of 5]

decent intro to quant and hft concepts, not very in-depth but provides some fundamental knowledge into the space. tone is very defensive when talking about hft which doesn't really further the author's argument. useful for a broad overview but nothing novel for people who have some experience in the industry.

[RJTK · Rating 4 out of 5]

Some of what is in here is patently wrong, but it is still not a bad book. It's also interesting that it downplays machine learning methods, but (at least on historical data) relatively simple machine learning systems, which could plausibly have been built at the time, would have absolutely printed money.

[Denis Kuznetsov]

The book is quite easy to read and can be finished in a couple of days. However, I found much of it oversimplified, even though I genuinely enjoyed specific chapters, particularly those discussing front-running in HFT. Despite the author's assertions, I largely felt this was indeed the reality, especially considering the repeated instances where he claimed otherwise.

[Marin Vlastelica P. · Rating 2 out of 5]

Very broad handwavey handling of the topic. Good top-level abstract view though, but I didn't like the writing style, things just get listed in some order and shortly explained without building proper knowledge or intuition. The statistical side of things is barely touched.

[Ali G · Rating 4 out of 5]

A good book to start and get a better perspective of the overall process of quantitative and HFT.
+ easy to read but not too shallow + touch some interesting idea

[Paco · Rating 2 out of 5]

It was a little be disappointing, the content was very basic and brief. In my opinion, the whole book could be perfectly summarized in a couple of pages.

[Damon Yuan · Rating 1 out of 5]

Superficial

[Robbie · Rating 5 out of 5]

4.5 nice intro to understanding the hidden traders of the mkt

[Bao Le · Rating 5 out of 5]

5 stars, must read to understand inside of quants

[Gabriel M · Rating 3 out of 5]

Plenty of useful material for beginners, some takeaways for intermediate readers, and maybe one or two insights for advanced practitioners.

[Claudio Martel · Rating 3 out of 5]

As the title says, it is a simple guide. And I think that emphasizing the title of the book and not expecting more from it than a simple guide is the best way to avoid any disappointment.

[Phil Toop · Rating 5 out of 5]

I enjoyed this book and found it gave a good rundown of what a quant is and what they do. It is written in a way that should be easy to follow for someone with little or no experience in markets.
The section on high frequency trading was fairly brief, but at the time of writing (2012) it was not as developed as it is now, and so perhaps there was less to write about.

[Hannah Sleath · Rating 4 out of 5]

Nice overview of quant trading, good for people wanting to get an idea of the bigger picture/people new to the field. Doesn’t go into any mathematical detail though, if that’s what you’re looking for

[Bill Zhang · Rating 4 out of 5]

Great book!