Using R to analyse MAN AHL Trend
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Let’s use the great PerformanceAnalytics package to get some insights on the risk profile of the MAN AHL Trend Fund. It’s a program with a long track record – I believe in the late 80′. The UCITS Fund NAV Data can be downloaded from the fund webpage as xls file- starting 2009.Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
First let’s import the data into R. I’m using a small function, to import .csv which returns an .xts object named ahl.
#Monthly NAV MAN AHL
loadahl<-function(){
a=read.table(“ahl_trend.csv”,sep = “,”,dec = “,”)
a$date = paste(substr(a$V1,1,2),substr(a$V1,4,5),substr(a$V1,7,10),sep=”-“)
ahl=a$date
ahl=cbind(ahl,substr(a$V2,1,5))
a=as.POSIXct(ahl[,1],format=”%d-%m-%Y”)
ahl=as.xts(as.numeric(ahl[,2]),order.by=a)
rm(a)
return(ahl)
}
next we would like to have the monthly returns
monthlyReturn(x, subset=NULL, type='arithmetic', leading=TRUE, ...)which we store in retahl.
retahl=monthlyReturn(ahl,type=”log”)
Next, I usually plot the chart.Drawdown to get a visual idea, if the product is designed for my risk appetite.
chart.Drawdown(retahl)
table.AnnualizedReturns(retahl) monthly.returns Annualized Return 0.0212 Annualized Std Dev 0.1246 Annualized Sharpe (Rf=0%) 0.1702 table.DownsideRisk(retahl) monthly.returns Semi Deviation 0.0254 Gain Deviation 0.0222 Loss Deviation 0.0222 Downside Deviation (MAR=10%) 0.0289 Downside Deviation (Rf=0%) 0.0241 Downside Deviation (0%) 0.0241 Maximum Drawdown 0.2478 Historical VaR (95%) -0.0521 Historical ES (95%) -0.0748 Modified VaR (95%) -0.0573 Modified ES (95%) -0.0730
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