More Thoughts on US Death Spiral
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
What troubles me most about today’s environment is the persistent belief that crisis large or small results in a US dollar rally and lower Treasury rates. However, what happens if the US dollar and US Treasury rates are the source of the crisis? Then the US enters a death spiral and the currency, stocks, and bonds suffer simultaneously and equally, and unfortunately there is nowhere in traditional asset allocation to hide.
Recent events are simply a phenomenon begun in 1998 with $4-$5 Trillion Asian Central Bank reserve building and local currency devaluation. There are limits to the monetary and fiscal policies pursued so vigorously since 2000, and I think we have found those limits and will face much more severe consequences.
For more see earlier posts:
New Favorite Test of US Monetary Policy Limits
 |
| From TimelyPortfolio |
 |
| From TimelyPortfolio |
 |
| From TimelyPortfolio |
If we look past 1998, the relationship looks much different.
 |
| From TimelyPortfolio |
 |
| From TimelyPortfolio |
 |
| From TimelyPortfolio |
require(quantmod)
require(PerformanceAnalytics) getSymbols("SP500",src="FRED")
getSymbols("DGS10",src="FRED")
getSymbols("DTWEXB",src="FRED")
getSymbols("DTWEXM",src="FRED") fedData <- na.omit(merge(SP500,DGS10,DTWEXB))
fedData <- merge(ROC(fedData[,1],type="discrete",n=1),
ROC(fedData[,2]/fedData[,3],type="discrete",n=1))
colnames(fedData) <- c("SP500","US10y/USDBroad") #jpeg(filename="performance since 2007.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.CumReturns(fedData["2007::"],legend.loc="bottomright",
main="SP500 and US 10y Rate/Broad Dollar Index")
#dev.off() #jpeg(filename="correlation.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.Correlation(fedData["2007::"],
main="SP500 and US 10y Rate/Broad Dollar Index
Correlation since 2007")
#dev.off() #jpeg(filename="rolling correlation.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.RollingCorrelation(fedData["2007::",1],fedData["2007::",2],n=250,
main="SP500 and US 10y Rate/Broad Dollar Index
Rolling 250 Day Correlation")
#dev.off() fedData <- na.omit(merge(SP500,DGS10,DTWEXM))
fedData <- merge(ROC(fedData[,1],type="discrete",n=1),
ROC(fedData[,2]/fedData[,3],type="discrete",n=1))
colnames(fedData) <- c("SP500","US10y/USDMajor") #jpeg(filename="performance.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.CumReturns(fedData,legend.loc="topleft",
main="SP500 and US 10y Rate/Broad Dollar Index")
#dev.off() #jpeg(filename="correlation.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.Correlation(fedData,
main="SP500 and US 10y Rate/Broad Dollar Index
Correlation Since 1973")
#dev.off() #jpeg(filename="rolling correlation.jpg",quality=100,
# width=6.25, height = 6.25, units="in",res=96)
chart.TimeSeries(runMean(runCor(fedData[,1],fedData[,2],n=250),n=250),
main="SP500 and US 10y Rate/Broad Dollar Index
Rolling 250 Day Average of Rolling 250 Day Correlation")
#dev.off()
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.