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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()
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