Overview of this book

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples.This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems.Starting with time series analysis, you will also learn how to optimize portfolios and how asset pricing models work. The book then covers fixed income securities and derivatives such as credit risk management.
Table of Contents (17 chapters)
Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Time Series Analysis
Portfolio Optimization
Asset Pricing Models
Fixed Income Securities
Estimating the Term Structure of Interest Rates
Derivatives Pricing
Credit Risk Management
Extreme Value Theory
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...