Financial risk modelling and portfolio optimization with R

Intro -- Title Page -- Copyright -- Table of Contents -- Preface to the Second Edition -- Preface -- Abbreviations -- About the Companion Website -- Part I: Motivation -- Chapter 1: Introduction -- Reference -- Chapter 2: A brief course in R -- 2.1 Origin and development -- 2.2 Getting help -- 2.3 Working with R -- 2.4 Classes, methods, and functions -- 2.5 The accompanying package FRAPO -- References -- Chapter 3: Financial market data -- 3.1 Stylized facts of financial market returns -- 3.2 Implications for risk models -- References -- Chapter 4: Measuring risks -- 4.1 Introduction -- 4.2 Synopsis of risk measures -- 4.3 Portfolio risk concepts -- References -- Chapter 5: Modern portfolio theory -- 5.1 Introduction -- 5.2 Markowitz portfolios -- 5.3 Empirical mean-variance portfolios -- References -- Part II: Risk modelling -- Chapter 6: Suitable distributions for returns -- 6.1 Preliminaries -- 6.2 The generalized hyperbolic distribution -- 6.3 The generalized lambda distribution -- 6.4 Synopsis of R packages for GHD -- 6.5 Synopsis of R packages for GLD -- 6.6 Applications of the GHD to risk modelling -- 6.7 Applications of the GLD to risk modelling and data analysis -- References -- Chapter 7: Extreme value theory -- 7.1 Preliminaries -- 7.2 Extreme value methods and models -- 7.3 Synopsis of R packages -- 7.4 Empirical applications of EVT -- References -- Chapter 8: Modelling volatility -- 8.1 Preliminaries -- 8.2 The class of ARCH models -- 8.3 Synopsis of R packages -- 8.4 Empirical application of volatility models -- References -- Chapter 9: Modelling dependence -- 9.1 Overview -- 9.2 Correlation, dependence, and distributions -- 9.3 Copulae -- 9.4 Synopsis of R packages -- 9.5 Empirical applications of copulae -- References -- Part III: Portfolio optimization approaches -- Chapter 10: Robust portfolio optimization -- 10.1 Overview.