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Quantitative Finance with R offers a winning strategy for devising expertly-crafted and workable trading models using the R open source programming language, providing readers with a step-by-step approach to understanding complex quantitative finance problems and building functional computer code.
- Sales Rank: #221079 in Books
- Published on: 2015-01-06
- Released on: 2015-01-06
- Original language: English
- Number of items: 1
- Dimensions: 9.62" h x .92" w x 6.20" l, 1.00 pounds
- Binding: Hardcover
- 272 pages
Review
"Through the lens of an expert practitioner, Harry provides a treatise on how to develop a robust quantitative trading strategy using 'R'. This is the first book written that has covered the ability of 'R' software to provide the infrastructure for an algorithmic trading system. Harry has written an instant classic that the professional and novice will find inherently useful. There is an inordinate amount of working 'R' code that the reader can deploy instantly or lever to develop more exotic functions and scripts. With this book, there is no need for expensive software development or a MATLAB license. Download the R software and you can begin building profitable strategies immediately. Harry has spawned an entire new generation of hedge fund managers with this seminal work." - Ed Zarek, Quantitative Options Trader, Chicago Volatility Group
"This is a superb text for aspiring quantitative traders. Financial math and computing concepts are introduced and developed simultaneously. The text guides readers through a set of R programming exercises that culminate in several data-based trading strategies. The conversational writing style and practitioner perspective will resonate with many readers." - Steven Todd, Associate Dean for Faculty and Research, Former Finance Department Chairperson, and Associate Professor Finance, Quinlan School of Business, Loyola University Chicago
"Quantitative Trading with R translates complicated topics into straightforward concepts. I'm using it as a reference and Belvedere has already incorporated some of the material into our classes." - Thomas Hutchinson, Managing Partner, Belvedere Trading, LLC
About the Author
Harry Georgakopoulos is a Professor of Quantitative Finance at Loyola University and Quantitative Trader at XR Trading, LLC. He has been working as a quantitative trader in Chicago, IL in the high frequency space since 2007. Prior to that, he was employed at Motorola and Andrew Corp. as an Electrical Engineer, where he designed and tested microwave transceivers for 3G mobile technologies, as well as at Milliman where he served as a Quantitative Financial Consultant. His main area of expertise is in the research and development of high-frequency, automated trading systems for futures and equities. He received his PhD in Financial Mathematics from The University of Chicago.
Most helpful customer reviews
44 of 47 people found the following review helpful.
Good, but not Great.
By Derek
As a quant I was excited to read this book based on previous reviews, and did enjoy reading it, but I want to make some statements about what I didn't like:
1. This book is very introductory. It could otherwise be considered an introduction to R. If you are comfortable with R for basic statistics and manipulating data, you likely won't learn anything new in the first half of the book. The second half of the book is where the meat lies.
2. The title falls (a little) short of expectation. I would have enjoyed more specifics in regards to quantitative trading, strategy development, algorithm design, back-testing, sensitivity analysis, etc... This includes showing more comprehensive examples and a more critical analysis of such examples. Perhaps if the author writes another book, this will be the focus. I just felt that the content wasn't thorough enough.
However, this book would be great for a student who plans on having a career in risk management or banking/trading, in a role where quantitative skills are required. For those who are already in the field, if you expect to learn beyond what you already know about R or quant trading, it may not be enough to satisfy your appetite. Keep in mind I've only elucidated my criticisms.
17 of 18 people found the following review helpful.
Too much, too little, and poorly edited.
By Brian C. Rakitin
While this book covers excellent material related to quantitative trading, it suffers from several problems.
First and foremost, it suffers from the ever increasingly common problem of poor editing. Function names are misspelled, variables names are mismatched between code and text, and figures are referenced by the wrong number. Code, tables and figures are often referred to as "below" when they aren't, and there are no numbers and multiple figures per page. Really amateur stuff.
As far as the content goes, it swings to wildly between overly simplified and ridiculously complex. For example, the introduction to statistics spends way to much time using the mean as an example, but then proceeds to a detailed yet too difficult description of bias, before abruptly pivoting to variance and variance-bias trade off in just a few lines.
The R code examples are well motivated but no one should fall for the authors pretense of this being accessible to beginners. Although well formed (if not always best written), the code is not described in sufficient detail in text.
Overall, this book could have used another round of editing and maybe 50 pages of additional material in the early chapters. Also, some of the later material should have been reworked and marketed to intermediate to advanced programmers with at least some background in quantitative finance.
15 of 16 people found the following review helpful.
editorial and program example errors hinder content
By Amazon Customer
In the first 2 chapters I found a number of serious editing errors. The first program examole s don't work as printed (although an experienced R coder can spot the problems fairly easily). Overall, nice content so far. But there is no link to the example programs (you have to type them by hand) and the book assumes you already have CSV files of the data in your disk (and in the proper format, with the right features/variables, etc). Hopefully the rest of the book improves dramatically. Because I want to like this book.
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