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Mastering R for Quantitative Finance

You're reading from   Mastering R for Quantitative Finance Use R to optimize your trading strategy and build up your own risk management system

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Length 362 pages
Edition 1st Edition
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Toc

Table of Contents (15) Chapters Close

Preface 1. Time Series Analysis FREE CHAPTER 2. Factor Models 3. Forecasting Volume 4. Big Data – Advanced Analytics 5. FX Derivatives 6. Interest Rate Derivatives and Models 7. Exotic Options 8. Optimal Hedging 9. Fundamental Analysis 10. Technical Analysis, Neural Networks, and Logoptimal Portfolios 11. Asset and Liability Management 12. Capital Adequacy 13. Systemic Risks Index

Core-periphery decomposition

Interbank markets are tiered and operate in a hierarchical fashion. It is a well-known characteristic of these markets that many banks are dealing with only a small number of big institutions, while these big institutions are acting like intermediaries or money-center banks. These big institutions are considered to be the core of the network, and the others are the periphery.

Many papers focused on this characteristic of real-world networks. For example, Borgatti and Everett (1999) examined this phenomenon on a network made of citation data, and found three journals to be the members of the core. Craig and von Peter (2010) used this core/periphery structure for the German interbank market. Their findings suggest that bank-specific features help to explain how banks position themselves in the interbank market. There is a strong correlation between the size and position in the network. As tiering is not random but behavioral, there are economic reasons (for example...

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