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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

Greeks


Understanding the risk-types that an option might involve is crucial for all market participants. The idea behind Greeks is to measure the different types of risks; they represent the sensitivity of the option to different factors. The Greeks of a plain vanilla option are: delta (, sensitivity to the underlying price), gamma (, sensitivity of delta to the underlying price, delta of delta), theta (, sensitivity to time), rho (, sensitivity to the risk-free rate), and vega (V, sensitivity to the volatility). In terms of mathematics, all Greeks are partial derivatives of the derivative price:

The Greeks can be computed easily for each option with the GBSGreeks function:

> sapply(c('delta', 'gamma', 'vega', 'theta', 'rho'), function(greek)
+   GBSGreeks(Selection = greek, TypeFlag = "c", S = 900, X = 950,
+     Time = 1/4, r = 0.02, b = 0.02, sigma = 0.22)
+ )
    delta         gamma          vega         theta           rho
0.347874404   0.003733069 166.308230868 -79.001505841  72...
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