Bonds are boring…read this

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.