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Mastering R for Quantitative Finance

You're reading from  Mastering R for Quantitative Finance

Product type Book
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Pages 362 pages
Edition 1st Edition
Languages

Table of Contents (20) Chapters

Mastering R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis 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

Summary


This chapter was about interest rate models and interest rate derivatives. After introducing the Black model, we used it to price caps and caplets. We also examined the R code for the Black-Scholes model.

Then, we turned our attention to interest rate models such as the Vasicek and CIR models. We discussed the theory of parameter estimation as well. At the end, we briefly demonstrated how the SMFI5 package works. Interest rate models were important for us in this chapter because the pricing of interest rate derivatives starts with assuming something about interest rates and yield curves in the future. With the help of a properly chosen and calibrated model, we have the opportunity to analyze possible future scenarios of the interest rates. Interest rate models are, of course, a much wider topic, which is worth studying in more detail. However, learning the most popular and well-known models is a good start, and we encourage you to study them further or check out the next chapter because...

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