**Timely Portfolio**, and kindly contributed to R-bloggers)

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The Fed is on a roll adding BAC ML Bond Indicies and now complete history for the four primary Dow Jones Indexes, so I wanted to extend my first post Long XLU Short SPY to add some more historical context. Unfortunately, the Dow Jones Indicies are only price return, but I think exploration still benefits the discussion. Including dividends significantly enhances the spread position.

From TimelyPortfolio |

Now with the US 10y Treasury price return series. See Historical Sources of Bond Returns-Comparison of Daily to Monthly for details on the US 10y Treasury return calculations.

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

The original discussion was as a bond manager what I can do if I do not like bonds. Lets have a quick look at the Long DJUA Short US10y price spread to see how it will work in this context. Correlations above are certainly attractive.

From TimelyPortfolio |

R code:

#get even more history

require(RQuantLib)

require(PerformanceAnalytics)

require(quantmod)

#first bonds

getSymbols(“DGS10″,src=”FRED”) #load daily US Treasury 10y from Fed Fred

DGS10pricereturn<-DGS10 #set this up to hold price returns

DGS10pricereturn[1,1]<-0

colnames(DGS10pricereturn)<-“PriceReturn-daily to monthly DGS10”

#I know I need to vectorize this but not qualified enough yet

#Please feel free to comment to show me how to do this

for (i in 1:(NROW(DGS10)-1)) {

DGS10pricereturn[i+1,1]<-FixedRateBondPriceByYield(yield=DGS10[i+1,1]/100,issueDate=Sys.Date(),

maturityDate= advance(“UnitedStates/GovernmentBond”, Sys.Date(), 10, 3),

rates=DGS10[i,1]/100,period=2)[1]/100-1

}

#total return will be the price return + yield/12 for one month

DGS10totalreturn<-DGS10pricereturn+lag(DGS10,k=1)/12/100

colnames(DGS10totalreturn)<-“Total Return-daily to monthly DGS10”

#now Dow Jones Indexes

getSymbols(“DJIA”,src=”FRED”) #load daily Dow Jones Industrial

getSymbols(“DJUA”,src=”FRED”) #load daily Dow Jones Utility

DJUADJIA<-DJUA/DJIA

retDJ<-na.omit(merge(ROC(DJUADJIA,1,type=”discrete”),ROC(DJIA,1,type=”discrete”),ROC(DJUA,1,type=”discrete”)))

colnames(retDJ)<-c(“DJIA”,”DJUA”,”DJUADJIAspread”)

charts.PerformanceSummary(retDJ,ylog=TRUE,

main=”DJIA, DJUA, and DJUA/DJIA Spread Price Return Analysis”,

colorset=c(“cadetblue”,”darkolivegreen3″,”goldenrod”))

#now add bonds to analysis

retToAnalyze<-na.omit(merge(ROC(DJIA,1,type=”discrete”),

ROC(DJUA,1,type=”discrete”),

ROC(DJUA/DJIA,1,type=”discrete”),

DGS10pricereturn))

colnames(retToAnalyze)<-c(“DJIA”,”DJUA”,”DJUADJIAspread”,”US10yPrice”)

charts.PerformanceSummary(retToAnalyze,ylog=TRUE,

main=”DJIA, DJUA, DJUA/DJIA Spread, and US 10y Price Return Analysis”,

colorset=c(“cadetblue”,”darkolivegreen3″,”goldenrod”,”gray70″))

chart.Correlation(retToAnalyze)

corDJUADJIAtoDJIA<-runCor(retDJ[,1],retDJ[,2],120)

corDJUADJIAtoBonds<-runCor(retToAnalyze[,3],retToAnalyze[,4],120)

chartSeries(DJUADJIA,TA=”addTA(corDJUADJIAtoDJIA);addTA(corDJUADJIAtoBonds)”,

theme=”white”,

name=”Long DJUA and Short DJIA with Correlation Analysis”)

#now let’s see how it looks as long xlu short bonds on price basis

priceBonds<-na.omit(cbind(DGS10pricereturn,rep(1,NROW(DGS10))))

priceBonds<-cumprod(priceBonds[,1]+priceBonds[,2])

DJUABonds<-na.omit(merge(DJUA,priceBonds))

DJUABonds<-DJUABonds[,1]/DJUABonds[,2]

chartSeries(DJUABonds, log=TRUE,

theme=”white”,

name=”Long DJUA and Short Bonds Price”)

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**Timely Portfolio**.

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