Introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book.
Financial Risk Modelling and Portfolio Optimization with R:
- Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field.
- Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies.
- Explores portfolio risk concepts and optimization with risk constraints.
- Enables the reader to replicate the results in the book using R code.
- Is accompanied by a supporting website featuring examples and case studies in R.
Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Table of Contents
Part I MOTIVATION 1
1 Introduction 3
2 A brief course in R 6
3 Financial market data 26
4 Measuring risks 34
5 Modern portfolio theory 43
Part II RISK MODELLING 51
6 Suitable distributions for returns 53
7 Extreme value theory 84
8 Modelling volatility 112
9 Modelling dependence 127
Part III PORTFOLIO OPTIMIZATION APPROACHES 153
10 Robust portfolio optimization 155
11 Diversification reconsidered 189
12 Risk-optimal portfolios 217
13 Tactical asset allocation 255
Appendix A Package overview 314
Appendix B Time series data 324
Appendix C Back-testing and reporting of portfolio strategies 338
Appendix D Technicalities 342