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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Summary
In this chapter, we presented a case study of how Extreme Value Theory methods can be used in R in a real-life risk management application. After briefly covering the theory of threshold exceedance models in EVT, we worked through a detailed example of fitting a model to the tails of the distribution of fire insurance claims. We used the fitted model to calculate high quantiles (Value at Risk) and conditional expectations (Expected Shortfall) for the fire losses. The presented methods are readily extendable to market, credit, or operational risk losses as well.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.