Introduction to R for Quantitative Finance

Table of contents

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