RSS 2.0


Examples for the second edition

The table below provides an overview of the available examples. For downloading the files do a right-click with your mouse on the link in the far right column.

Example Description Download
R code Gzipped tarball of examples tarball
R code 2.1 The package FRAPO C2R1.R
R code 3.1 Stylised Facts of the Returns for Siemens C3R1.R
R code 3.2 Stylised Facts of European Equity Market C3R2.R
R code 6.1 Fitting HPW-returns to the GHD C6R1.R
R code 6.2 VaR and ES derived from the GHD, HYP and NIG C6R2.R
R code 6.3 Shape triangle for HYP distribution C6R3.R
R code 6.4 VaR of QRM Stock: Comparison of GLD and Normal distribution C6R4.R
R code 6.5 FTSE 100 Stocks: Shape triangle of standardised GLD C6R5.R
R code 7.1 Block maxima for the losses of Siemens C7R1.R
R code 7.2 r-Block Maxima for the losses of BMW C7R2.R
R code 7.3 POT-GPD for the losses of Boeing C7R3.R
R code 7.4 De-clustering of NYSE exceedances C7R4.R
R code 8.1 Expected shortfall derived from GARCH(1,1) models C8R1.R
R code 9.1 GARCH-Copula: Expected shortfall C9R1.R
R code 9.2 Mixing of copulae: Clayton and Gumbel C9R2.R
R code 10.1 Portfolio simulation: data generation C10R1.R
R code 10.2 Portfolio simulation: function for estimating moments C10R2.R
R code 10.3 Portfolio simulation: estimates for data processes C10R3.R
R code 10.4 Portfolio simulation: minimum-variance optimisations C10R4.R
R code 10.5 Portfolio back-test: descriptive statistics of returns C10R5.R
R code 10.6 Portfolio back test: rolling window optimisation C10R6.R
R code 10.7 Robust portfolio optimisation with elliptical uncertainty C10R7.R
R code 10.8 Efficient frontiers for mean-variance and robust counterpart optimization with elliptical uncertainty of μ C10R8.R
R code 10.9 Determining equivalent mean-variance allocation for a given robust counterpart risk weighting C10R9.R
R code 10.10 Graphical display of efficient frontier for mean-variance and roubust counterpart portfolios C10R10.R
R code 11.1 Comparison of portfolio solution for Swiss equity sectors C11R1.R
R code 11.2 Key measures of portfolio solutions for Swiss equity sectors C11R2.R
R code 11.3 S&P 500: Tail-dependence versus low-β portfolio C11R3.R
R code 11.4 Plotting of wealth progression and relative performance C11R4.R
R code 11.5 Key measures of portfolio solutions for S&P 500 C11R5.R
R code 11.6 Comparison of restricted ES-portfolios with GMV and ERC C11R6.R
R code 12.1 Minimum-CVaR vs. minimum-variance portfolios: back-test C12R1.R
R code 12.2 Plotting of wealth trajectory C12R2.R
R code 12.3 Comparison of draw-down and GMV portfolios C12R3.R
R code 12.4 Analysis of portfolio solutions C12R4.R
R code 12.5 Back-test: GMV versus CDaR portfolio optimisation C12R5.R
R code 12.6 Back-test: evaluation of results, part one C12R6.R
R code 12.7 Back-test: Evaluation of results, part two C12R7.R
R code 12.8 Risk surface plot of multi-asset portfolio, part one C12R8.R
R code 12.9 Risk surface plot of multi-asset portfolio, part two C12R9.R
R code 12.10 Risk surface plot of multi-asset portfolio, part three C12R10.R
R code 13.1 Integration and co-integration analysis of equity indexes C13R1.R
R code 13.2 Generating views derived from VAR model of assets C13R2.R
R code 13.3 Maximum Sharpe ratio portfolio specifications C13R3.R
R code 13.4 Maximum Sharpe ratio portfolio back-test C13R4.R
R code 13.5 Comparison of portfolio strategies C13R5.R
R code 13.6 Display of portfolio strategies C13R6.R
R code 13.7 Copula opinion pooling C13R7.R
R code 13.8 Copula opinion pooling: densities C13R8.R
R code 13.9 Comparison of portfolio allocations C13R9.R
R code 13.10 Data preparation C13R10.R
R code 13.11 Definition of forecast and entropy pooling functions C13R11.R
R code 13.12 Back-testing portfolio strategies C13R12.R
R code 13.13 Analysis of results C13R13.R
R code 13.14 Data preparation C13R14.R
R code 13.15 Forecasting model C13R15.R
R code 13.16 Risk model C13R16.R
R code 13.17 Formulation of linear program C13R17.R
R code 13.18 Portfolio simulation C13R18.R
R code 13.19 Comparison of portfolio allocations C13R19.R
R code 14.1 Monte Carlo integration methods for probabilistic utility function C14R1.R
R code 14.2 Simulation of Markov chains C14R2.R
R code 14.3 Metropolis-Hastings: comparison of independence and random walk sampler C14R3.R
R code 14.4 Definition of the utility function C14R4.R
Stan code 14.1 Definition of the utility function in the Stan language C14S1.stan
R code 14.5 Probabilistic versus maximized expected utility, part one C14R5.R
R code 14.6 Probabilistic versus maximized expected utility, part two C14R6.R
R code 14.7 Utility simulation C14R7.R
R code 14.8 Graphical analysis of utility simulation C14R8.R
R code 14.9 Allocation analysis of utility simulation C14R9.R