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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 Black-Scholes model


The assumptions of the Black-Scholes model (Black and Sholes, 1973, see also Merton, 1973) are as follows:

  • The price of the underlying asset (S) follows geometric Brownian motion:

    Here µ (drift) and σ (volatility) are constant parameters and W is a standard Wiener process.

  • The market is arbitrage-free.

  • The underlying is a stock paying no dividends.

  • Buying and (short) selling the underlying asset is possible in any (even fractional) amount.

  • There are no transaction costs.

  • The short-term interest rate (r) is known and constant over time.

The main result of the model is that under these assumptions, the price of a European call option (c) has a closed form:

  • ,
  • ,

Here X is the strike price, T-t is the time to maturity of the option, and N denotes the cumulative distribution function of the standard normal distribution. The equation giving the price of the option is usually referred to as the Black-Scholes formula. It is easy to see from put-call parity that the price of a European...

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