Introduction to R for Quantitative Finance -- Table of Contents -- Introduction to R for Quantitative Finance -- Credits -- About the Authors -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Time Series Analysis -- Working with time series data -- Linear time series modeling and forecasting -- Modeling and forecasting UK house prices -- Model identification and estimation -- Model diagnostic checking -- Forecasting -- Cointegration -- Cross hedging jet fuel -- Modeling volatility -- Volatility forecasting for risk management -- Testing for ARCH effects -- GARCH model specification -- GARCH model estimation -- Backtesting the risk model -- Forecasting -- Summary -- 2. Portfolio Optimization -- Mean-Variance model -- Solution concepts -- Theorem (Lagrange) -- Working with real data -- Tangency portfolio and Capital Market Line -- Noise in the covariance matrix -- When variance is not enough -- Summary -- 3. Asset Pricing Models -- Capital Asset Pricing Model -- Arbitrage Pricing Theory -- Beta estimation -- Data selection -- Simple beta estimation -- Beta estimation from linear regression -- Model testing -- Data collection -- Modeling the SCL -- Testing the explanatory power of the individual variance -- Summary -- 4. Fixed Income Securities -- Measuring market risk of fixed income securities -- Example - implementation in R -- Immunization of fixed income portfolios -- Net worth immunization -- Target date immunization -- Dedication -- Pricing a convertible bond -- Summary -- 5. 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 -- 6. Derivatives Pricing -- The Black-Scholes model -- The Cox-Ross-Rubinstein model -- Connection between the two models -- Greeks -- Implied volatility -- Summary -- 7. Credit Risk Management -- Credit default models -- Structural models -- Intensity models -- Correlated defaults - the portfolio approach -- Migration matrices -- Getting started with credit scoring in R -- Summary -- 8. Extreme Value Theory -- Theoretical overview -- Application - modeling insurance claims -- Exploratory data analysis -- Tail behavior of claims -- Determining the threshold -- Fitting a GPD distribution to the tails -- Quantile estimation using the fitted GPD model -- Calculation of expected loss using the fitted GPD model -- Summary -- 9. 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 -- A. References -- Time series analysis -- Portfolio optimization -- Asset pricing -- Fixed income securities -- Estimating the term structure of interest rates -- Derivatives Pricing -- Credit risk management -- Extreme value theory -- Financial networks -- Index.