Rasio Sharpe (tahunan)
Pengantar Analisis Portofolio di R
Kris Boudt
Professor, Free University Brussels & Amsterdam
Patokan kinerja
Patokan kinerja
Trade-off risiko-imbal hasil
Trade-off risiko-imbal hasil
Trade-off risiko-imbal hasil
Trade-off risiko-imbal hasil
Trade-off risiko-imbal hasil
Trade-off risiko-imbal hasil
Garis alokasi modal
Garis alokasi modal
Garis alokasi modal
Garis alokasi modal
Rasio Sharpe
Rasio Sharpe
Rasio Sharpe
Rasio Sharpe
Statistik kinerja: praktik
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Statistik kinerja: praktik
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
mean(sample_returns)
Statistik kinerja: praktik
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)
Statistik kinerja: praktik
library(PerformanceAnalytics)
sample_returns <- c(-0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
StdDev(sample_returns)
Statistik kinerja: praktik
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)
Tahunkan kinerja bulanan
- Rata-rata aritmetika: rata-rata bulanan * 12
- Rata-rata geometri, saat $R_i$ adalah imbal hasil bulanan:
- $[(1+R_1)\cdot(1+R_2)\cdot...\cdot(1+R_T)]^{12/T} -1$
- Volatilitas: volatilitas bulanan * sqrt(12)
Statistik kinerja: praktik
library(PerformanceAnalytics)
sample_returns <- c( -0.02, 0.00, 0.00, 0.06, 0.02, 0.03, -0.01, 0.04)
Statistik kinerja: praktik
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)
Statistik kinerja: praktik
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)
Statistik kinerja: praktik
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)
Statistik kinerja: praktik
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)
