Quantitative Trading With R: Understanding Mathematical And Computational Tools From A Quant's Perspective Download Free (EPUB, PDF)
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.
Hardcover: 272 pages
Publisher: Palgrave Macmillan; 2015 edition (January 6, 2015)
Language: English
ISBN-10: 1137354070
ISBN-13: 978-1137354075
Product Dimensions: 6.2 x 0.9 x 9.6 inches
Shipping Weight: 1.2 pounds (View shipping rates and policies)
Average Customer Review: 4.4 out of 5 stars See all reviews (31 customer reviews)
Best Sellers Rank: #199,882 in Books (See Top 100 in Books) #43 in Books > Textbooks > Business & Finance > Banking #73 in Books > Business & Money > Investing > Commodities #93 in Books > Business & Money > International > Foreign Exchange
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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