November 2013
Beginner
164 pages
3h 46m
English
book
Introduction to R for Quantitative Finance
by Gergely Daróczi, Michael Phule, Edina Berlinger (EURO), Peter Csoka, Daniel Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Váradi, Agnes Vidovics-Dancs, Agnes Vidovics Dancs
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Solution concepts
In the last 50 years, many great algorithms have been developed for numerical optimization and these algorithms work well, especially in case of quadratic functions. As we have seen in the previous section, we only have quadratic functions and constraints; so these methods (that are implemented in R as well) can be used in the worst case scenarios (if there is nothing better).
However, a detailed discussion of numerical optimization is out of the scope of this book. Fortunately, in the special case of linear and quadratic functions and constraints, these methods are unnecessary; we can use the Lagrange theorem from the 18th century.
Theorem (Lagrange)
If and , (where ) have continuous partial derivatives and is a relative extreme ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.