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Introduction to R for Quantitative Finance

You're reading from   Introduction to R for Quantitative Finance R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781783280933
Length 164 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis FREE CHAPTER 2. Portfolio Optimization 3. Asset Pricing Models 4. Fixed Income Securities 5. Estimating the Term Structure of Interest Rates 6. Derivatives Pricing 7. Credit Risk Management 8. Extreme Value Theory 9. Financial Networks References Index

Contribution to systemic risk – identification of SIFIs


A complex system is not simply the sum of its elements. It is possible that all entities are safe in themselves, but the system as a whole is still vulnerable. Systemic risk is the risk of the entire system collapsing due to one or several shocks. If we wish to identify the systemically important financial institutions (SIFIs) as it was proposed by BCBS (2011), we have to consider five factors contributing to systemic risk: size, interconnectedness, lack of substitutes, cross-jurisdictional activity, and complexity of the activities. When measuring interconnectedness, we can rely on network data and can apply several methods, for example, centrality measures, stress test, and core-periphery models.

Now, we illustrate the first method based on an index of some centrality measures, as described in Komárková et al.(2012) and von Peter (2007). Banks with the highest index-value can be considered as the most central ones, thus with the most...

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