rplotvarrisk-analysis

How to combine VaR graphics?


I want to programm a rolling Value at Risk by hand. So I don't want to use the VaR from the PerformanceAnalytics package. I want to plot after calculations against the log-returns of a time series. Input:

getSymbols('^GDAXI', src='yahoo', return.class='ts',from="2005-01-01", to="2015-01-01")
GDAXI.DE=GDAXI[ , "GDAXI.Close"]
log_r1=diff(log(GDAXI.DE)) #log_r1=data
alpha=0.95

The VaR function:

VatR=function(data, alpha)
{
x=diff(log(data))  
mu=mean(x)
sigma=sqrt(var(x))
quant=qnorm(alpha, mean=0, sd=1)
vatr=tail(data,n=1)*(1-exp((-sigma)*quant+mu))    
}

data=GDAXI.DE
alpha=0.95
t=125
l=(-1)*diff(data)  #if GDAXI used code must be changed here diff
loss=c(0,l)
ValueatRisk=matrix(rep(0),length(data),1)
violations=matrix(rep(0),length(data),1)
for(i in (t+1):length(data))
{
ValueatRisk[i]=VatRnorm(data[(i-t):(i-1)] ,alpha)     #failure source
violations[i]=(loss[i] > ValueatRisk[i])
}

outputtheo=(1-alpha)*(length(data)-t) 
print(outputtheo)
outputreal=sum(violations)
print(outputreal)

I want to combine these graphics. It seems to be a scaling problem, I tried qplot, ggplot and so on without success.

graph1=plot(loss[(t+1):length(data)], type="l", col="blue")
graph2=plot(ValueatRisk[(t+1):length(data)], type="l", col="red")

How to bring them together in one plot?


Solution

  • If plotting is the only issue now, I think this will produce what you want.

    plot(loss[(t+1):length(data)], type="l", col="blue")
    lines(ValueatRisk[(t+1):length(data)], type="l", col="red")
    

    (And BTW, your code won't run as is because VatRnorm() inside the loop is really the old/original VatR().)