Quantitative Trading With R Understanding Mathematical Pdf

Quantitative Trading with R: Understanding Mathematical and Computational Tools from a Quant's Perspective
Author: Visit 's Harry Georgakopoulos Page ID: 1137354070

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 Quantitative Trader at a Chicago proprietary trading firm, as well as a part-time Adjunct Lecturer in Quantitative Finance at Loyola University. He has been working as a quant in the high frequency space since 2007. Prior to that, he worked as an RF Electrical Engineer at Motorola and Andrew Corporation where he designed and tested microwave transceivers for mobile technologies. His main area of expertise is in the research and development of automated trading systems for futures, equities, and options. He received his Master's in Financial Mathematics from the University of Chicago and also holds a Master's degree in Electrical Engineering.

Hardcover: 292 pagesPublisher: Palgrave Macmillan (January 6, 2015)Language: EnglishISBN-10: 1137354070ISBN-13: 978-1137354075 Product Dimensions: 6.2 x 0.9 x 9.6 inches Shipping Weight: 1.2 pounds (View shipping rates and policies) Best Sellers Rank: #45,774 in Books (See Top 100 in Books) #17 in Books > business & Money > International > Foreign Exchange #21 in Books > Business & Money > investing > Commodities #23 in Books > Business & Money > Investing > Analysis & Strategy
This title is getting 5 starts simply because there's no where else this information is in written down. (At least not outside the internal and highly guarded libraries of proprietary trading groups and hedge funds.)

So the book is a guide and a workbook for making a trading strategy. A coherent strategy that seasoned professionals won't laugh at you for in case you're trying to talk them in to letting you run your own show, or borrow money. You can say: "But look, my nonstationary timeseries have been transformed to log returns, the pairs trade is cointegrated, I've used total least squares regression to find the hedge ratio, and look at this risk, this Sortino ratio is gorgeous!"

On the good side the book is full of Notes, References and Tutorial suggestions. The Notes have a separate section from the References and the Tutorial and other suggestions are in the text. It's a thoughtful style in case you want to jump off an learn more about hedge ratios, or if you want more information on an R package…

On the bad side I'll have to complain for a moment about the section on Backtesting. It's a bit rushed. Backtesting often results in a false positive – that is, your backtester tells you the strategy is profitable when really, it's not. There needs to be a discussion on when to stop the strategy. The other side of a backtesting result are false negatives. This is almost never discussed anywhere: It's when your backtesting results in a loss but in real life the strategy would've been a winner. (A useful test of a backtester is to give it a winning strategy and see what it spits back at you.)

One of the exciting things about any book is where you can go and what you can do after you've read it.
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