Bonds are boring…read this

December 8, 2014
By

(This article was first published on Copula, and kindly contributed to R-bloggers)

If you would have invested in 1992 in the DAX ETF – provided it would have been around, of course – you would have earned a decent amount of money.

That’s the story of the passive guys and in my previous post I’m borrowing a few arguments of this guys to support Buy & Hold.

I’m sure you know the problem, when you wish to backtest a new strategy over a long period and you don’t have enough observations available.

My Bond – Data Proxy is usually Pimco Total Return (PTTRX) and if you believe Bonds are boring read more.

Let’s first get Yahoo Data

library(quantmod)
library(PerformanceAnalytics)
library(TTR)

tickers=c(“^GDAXI”,”PTTRX”)
initDate=”1992-01-01″
  to = “2014-11-30”
  ticker=tickers
  #————————————————-
  suppressWarnings(try(getSymbols(ticker, index.class=”POSIXct”, from=initDate, to=to,src=”yahoo”),silent=TRUE))

Next let’s get the daily Returns

dax=ROC(GDAXI[,6],n=1,na.pad=T)
bonds=ROC(PTTRX[,6],n=1,na.pad=T)

Now, this might hold the first surpise

Return.annualized(dax)
GDAXI.Adjusted
Annualized Return 0.05474645
 
Return.annualized(renten)
PTTRX.Adjusted
Annualized Return 0.06626953
 
 
Are bonds still boring?
 
Read on
 
portf=cbind(dax,renten)  

table.CalendarReturns(portf, digits = 1, as.perc = TRUE, geometric = TRUE)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec GDAXI.Adjusted PTTRX.Adjusted
1992 0.4 -0.3 0.4 -0.1 0.5 -0.3 -0.5 1.6 -0.7 -0.1 1.4 0.2 2.6 6.9
1993 0.3 1.5 -0.1 0.2 -0.2 -0.6 -1.7 1.2 0.4 1.5 0.7 2.3 5.7 5.0
1994 2.0 0.8 -0.7 -0.2 0.4 -1.0 1.1 0.1 -1.6 1.5 0.2 1.4 4.1 6.0
1995 -0.7 0.1 0.2 -0.5 0.2 -1.1 -0.5 -0.1 0.7 1.0 -0.1 -1.0 -1.7 9.3
1996 1.4 0.0 -0.9 0.0 0.6 0.4 0.6 -0.6 -0.3 -0.7 1.0 1.2 2.7 6.7
1997 0.6 -0.5 0.3 1.6 -2.0 -1.1 -1.2 0.6 0.9 0.1 0.3 -1.0 -1.5 8.0
1998 0.0 0.0 0.5 0.0 1.6 -0.3 -0.1 -3.2 -2.3 2.6 -1.9 -0.6 -3.9 8.0
1999 1.2 -0.9 0.6 1.1 0.0 0.4 1.0 -2.3 0.3 0.8 0.1 1.4 3.7 6.9
2000 -3.3 0.8 -0.6 2.6 -0.1 0.0 0.9 0.7 -0.5 2.2 -3.5 1.0 -0.1 8.5
2001 0.8 -0.2 -0.8 1.4 1.3 1.4 1.2 0.5 2.9 0.3 1.1 0.8 11.4 7.9
2002 1.1 1.6 0.9 0.7 1.2 2.8 -4.7 1.4 -5.3 1.3 -1.2 1.8 1.2 5.0
2003 2.0 1.3 -3.9 1.1 2.6 -0.1 1.7 -0.2 -2.0 0.4 0.0 0.3 3.1 3.5
2004 -0.9 0.3 -0.4 -0.6 0.5 -0.4 0.2 -1.4 -0.7 0.0 -0.5 0.2 -3.8 4.3
2005 1.3 0.0 0.0 0.2 -0.4 0.1 -0.1 0.8 0.5 2.1 -0.1 -0.9 3.3 3.7
2006 0.2 -2.0 -0.2 -1.0 1.2 1.8 -0.4 -0.1 0.3 0.2 -0.9 -0.2 -1.2 5.9
2007 0.0 -1.5 0.3 0.4 1.5 1.1 1.7 1.6 0.1 0.5 1.3 0.4 7.5 5.6
2008 -0.3 -1.7 -0.4 0.9 0.6 -0.1 0.3 0.0 0.4 2.4 0.1 2.2 4.5 6.0
2009 -2.0 -2.5 2.4 1.4 0.2 -1.6 -0.5 -1.1 -0.7 -3.1 -1.1 -0.9 -9.4 7.3
2010 1.2 1.2 0.2 -0.1 0.3 0.2 0.2 0.2 -0.3 0.1 -0.1 0.0 3.1 4.9
2011 -0.4 1.2 -0.2 0.5 1.8 1.1 -0.4 2.5 -2.5 -3.3 4.9 0.8 6.0 5.7
2012 0.2 -0.5 1.0 -0.6 -0.3 4.2 0.0 1.1 -1.0 -0.3 0.1 0.0 3.9 4.0
2013 -0.5 0.9 0.1 0.5 -0.6 -0.4 0.1 -1.1 -0.8 0.3 0.2 -0.4 -1.8 1.7
2014 -0.7 1.1 -0.3 0.2 0.0 0.2 -2.0 0.1 0.5 2.3 0.1 NA 1.4 2.2
 
maxDrawdown(dax)
[1] 0.7669261
 
 
maxDrawdown(renten)
[1] 0.1053507


Revealing, isn't it. 
 

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