PacktLib: Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance

Credits

About the Authors

About the Reviewers

www.PacktPub.com

Preface

Time Series Analysis

Working with time series data

Linear time series modeling and forecasting

Cointegration

Modeling volatility

Summary

Portfolio Optimization

Mean-Variance model

Solution concepts

Working with real data

Tangency portfolio and Capital Market Line

Noise in the covariance matrix

When variance is not enough

Summary

Asset Pricing Models

Capital Asset Pricing Model

Arbitrage Pricing Theory

Beta estimation

Model testing

Summary

Fixed Income Securities

Measuring market risk of fixed income securities

Immunization of fixed income portfolios

Pricing a convertible bond

Summary

Estimating the Term Structure of Interest Rates

The term structure of interest rates and related functions

The estimation problem

Estimation of the term structure by linear regression

Cubic spline regression

Applied R functions

Summary

Derivatives Pricing

The Black-Scholes model

The Cox-Ross-Rubinstein model

Connection between the two models

Greeks

Implied volatility

Summary

Credit Risk Management

Credit default models

Correlated defaults – the portfolio approach

Migration matrices

Getting started with credit scoring in R

Summary

Extreme Value Theory

Theoretical overview

Application – modeling insurance claims

Summary

Financial Networks

Representation, simulation, and visualization of financial networks

Analysis of networks’ structure and detection of topology changes

Contribution to systemic risk – identification of SIFIs

Summary

References

References

References

References

References

References

References

References

References

References

Index