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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

Connection between the two models


After applying the two basic option pricing models, we give some theoretical background to them. We do not aim to give a detailed mathematical derivation, but we intend to emphasize (and then illustrate in R) the similarities of the two approaches. The financial idea behind the continuous and the binomial option pricing is the same: if we manage to hedge the option perfectly by holding the appropriate quantity of the underlying asset, it means we created a risk-free portfolio. Since the market is supposed to be arbitrage-free, the yield of a risk-free portfolio must equal the risk-free rate. One important observation is that the correct hedging ratio is holding underlying asset per option. Hence, the ratio is the partial derivative (or its discrete correspondent in the binomial model) of the option value with respect to the underlying price. This partial derivative is called the delta of the option. Another interesting connection between the two models...

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