Die (annualisierte) Sharpe Ratio
Einführung in die Portfolioanalyse in R
Kris Boudt
Professor, Free University Brussels & Amsterdam
Performance benchmarken
Performance benchmarken
Rendite-Risiko-Abwägung
Rendite-Risiko-Abwägung
Rendite-Risiko-Abwägung
Rendite-Risiko-Abwägung
Rendite-Risiko-Abwägung
Rendite-Risiko-Abwägung
Capital Allocation Line
Capital Allocation Line
Capital Allocation Line
Capital Allocation Line
Die Sharpe Ratio
Die Sharpe Ratio
Die Sharpe Ratio
Die Sharpe Ratio
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
mean(sample_returns)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
mean.geometric(sample_returns)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
StdDev(sample_returns)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
(mean(sample_returns)-0.004)/StdDev(sample_returns)
Monatliche Performance annualisieren
- Arithmetisches Mittel: monatlicher Mittelwert * 12
- Geometrisches Mittel, wenn $R_i$ monatliche Renditen sind:
- $[(1+R_1)\cdot(1+R_2)\cdot...\cdot(1+R_T)]^{12/T} -1$
- Volatilität: monatliche Volatilität * sqrt(12)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Return.annualized(sample_returns, scale = 12, geometric = FALSE)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Return.annualized(sample_returns, scale = 12, geometric = TRUE)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Std.Dev.annualized(sample_returns, scale = 12)
Performancemaße in Aktion
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Return.annualized(sample_returns, scale = 12)/
Std.Dev.annualized(sample_returns, scale = 12)
