Skew of Bonds

As the researchpuzzler highlights in “a bad bet”, US bonds were a popular subject at the CFA Institute Annual Conference.  While US Bonds have been in an amazing 30 year run (see previous posts Lattice Explore Bonds, Bond Market as a Casino Game Part 1, Calmar Ratio 1.37 over the past 20 years), I think many positive skew-chasing market participants are not aware of the frequency of negative skew in bond returns.  As a public service, I thought I should issue a negative skew alert.

From TimelyPortfolio

R code from GIST:

	require(quantmod)
	require(PerformanceAnalytics)
	#load my barclays agg file
	#if you do not have access to Barclays Agg return then you can
	#use VBMFX as a proxy
	portfolio <- read.csv("C:\\Users\\Kent.TLEAVELL_NT\\Documents\\old\\R\\barclaysagg.csv",stringsAsFactors=FALSE)
	portfolio <- portfolio[2:(NROW(portfolio)-1),2:NCOL(portfolio)]
	portfolio <- portfolio[,c(1,4)]
	#since export has duplicate colnames we need to remove the .1 added
	#colnames(portfolio) <- substr(colnames(portfolio),1,nchar(colnames(portfolio))-2)
	#transform to get in appropriate xts form
	len <- nchar(portfolio[,1])
	xtsdate <- paste(substr(portfolio[,1],len-3,len),"-",
	ifelse(len==9,"0",""),substr(portfolio[,1],1,len-8),"-01",sep="")
	portfolio.xts <- xts(data.matrix(portfolio[,2:NCOL(portfolio)]),order.by=as.Date(xtsdate))
	portfolio.xts <- portfolio.xts/100
	portfolio.xts[1,]<-0
	#########start skew analysis################################################
	colnames(portfolio.xts) <- "BarclaysAgg"
	#get rolling skew
	skew <- apply.rolling(portfolio.xts[,1],FUN=skewness,width=36,by=1)
	#combine skew with ROC
	skew.roc <- merge(skew,
	ROC(apply(portfolio.xts[,1]+1,MARGIN=2,FUN=cumprod),type="discrete",n=36))
	colnames(skew.roc)<-c("skew","roc")
	#plot skew and roc
	chart.TimeSeries(skew.roc, main="Barclays US Aggregate Skew and ROC (Rolling 36-month)",
	legend.loc="topright")

view raw bond skew.r hosted with ❤ by GitHub