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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

The estimation problem


We cannot observe the term structure directly, but we can observe the market prices of instruments whose price depends on the term structure and thus estimate the term structure. A good source of information regarding the term structure is the government bond market, where usually a lot of liquid securities are traded whose prices depend solely on the term structure.

Suppose there are n bonds traded whose gross (or dirty) prices are denoted by . There are m dates when at least one bond's owners receive a payment. These payments are due in years time respectively where . The matrix C contains the cash flows of the bonds. We model bond prices as the sum of the present value of the bond's cash flow and a normally distributed error term:

Here d is the vector containing the discount factors and is a vector containing the error terms. The observed market price of a bond can differ from the present value of the cash flow for two reasons: there might be a measurement error...

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