drawdown and system success.r

require(ttrTests)
require(quantmod)
require(PerformanceAnalytics)

#simple price crossover moving average system
#style slightly different to conform to ttrTests
oneSMA <- function(x,params=10,burn=0,short=FALSE) {
mac2<-runMean(x,params[1])
sig<-ifelse(x>=mac2,1,0)
sig[is.na(sig)]<-0
return(sig)
}

getSymbols("^GSPC",from="1896-01-01",to=Sys.Date())
price.monthly<-to.monthly(GSPC)[,4]
price.vector<-as.vector(price.monthly)

bsamples=100000 #this takes a while; choose smaller for playing
#prepopulate results matrix with NA
#for quicker filling later
results = matrix(nrow=bsamples,ncol=8)
colnames(results) <- c("Drawdown.Sample","Drawdown.System",
	"Return.Sample","Return.System","SD.Sample","SD.System",
	"Skewness.Sample","Skewness.System")
for (i in 1:bsamples) {
	sample<-generateSample(price.vector)
	ret <- as.vector(cReturns(sample,ttr=oneSMA, params=10, burn=0, short=FALSE)[[1]])

	results[i,1] <- maxDrawdown(
		as.xts(ROC(sample,type="discrete",n=1),order.by=index(price.monthly))
		)
	results[i,2] <- maxDrawdown(
		as.xts(ret,order.by=index(price.monthly))
		)
	results[i,3] <- sample[NROW(sample)]/sample[1]-1
	results[i,4] <- cumprod(1+ret)[length(ret)]-1
	results[i,5] <- sd(ROC(sample,type="discrete",n=1,na.pad=FALSE))
	results[i,6] <- sd(ret)
	results[i,7] <- skewness(ROC(sample,type="discrete",n=1,na.pad=FALSE))
	results[i,8] <- skewness(ret)
}

par(mfrow=c(2,1)) #2 rows and 1 columns for the boxplot
bpdraw <- boxplot((results[,4]-results[,3])~round(results[,1],1),
	stats=TRUE, main="Boxplot of System Outperformance by Drawdown")
bpsd <- boxplot((results[,4]-results[,3])~round(results[,5],3),
	stats=TRUE, main="Boxplot of System Outperformance by Std. Dev.")

#check plot of drawdown versus standard deviation
plot(results[,1]~results[,5],pch=16,col="cadetblue4")
abline(lm(results[,1]~results[,5]),col="indianred",lwd=2)

chart.Correlation(cbind(results,results[,6]-results[,5]))

par(mfrow=c(2,1)) #2 rows and 1 columns for the density plots
#do the density plot for drawdown
d1 <- density(results[,1])
d2 <- density(results[,2])
plot( d2, col=2, lwd=3, main="Density Plot of Sample and System Drawdown")
lines( d1, col=4, lwd=3)
abline(v=maxDrawdown(ROC(price.monthly,type="discrete",n=1)),col="grey70")
text(x=maxDrawdown(ROC(price.monthly,type="discrete",n=1)), y=3.7, pos=3,
	labels="SP500",srt=90,col="grey70", cex=0.75)
legend("topright",legend=c("System","Sample"),col=c(2,4),lwd=3,bty="n")
#do the density plot for standard deviation
d1 <- density(results[,5])
d2 <- density(results[,6])
plot( d2, col=2, lwd=3, xlim=c(min(d2$x),max(d1$x)),
	main="Density Plot of Sample and System Std. Dev.")
lines( d1, col=4, lwd=3)
abline(v=sd(ROC(price.monthly,type="discrete",n=1,na.pad=FALSE)),col="grey70")
text(x=sd(ROC(price.monthly,type="discrete",n=1,na.pad=FALSE)), y=3.7, pos=3,
	labels="SP500",srt=90,col="grey70", cex=0.75)
legend("topright",legend=c("System","Sample"),col=c(2,4),lwd=3,bty="n")