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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

Chapter 4. Fixed Income Securities

In Chapter 3, Asset Pricing Models, we focused on models establishing a relationship between the risk measured by its beta, the price of financial instruments, and portfolios. The first model, CAPM, used an equilibrium approach, while the second, APT, has built on the no-arbitrage assumption.

The general objective of fixed income portfolio management is to set up a portfolio of fixed income securities with a given risk/reward profile. In other words, portfolio managers are aiming at allocating their funds into different fixed income securities, in a way that maximizes the expected return of the portfolio while adhering to the given investment objectives.

The process encompasses the dynamic modeling of the yield curve, the prepayment behavior, and the default of the securities. The tools used are time series analysis, stochastic processes, and optimization.

The risks of fixed income securities include credit risk, liquidity risk, and market risk among others...

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