table.Drawdowns {PerformanceAnalytics}

Worst Drawdowns Summary: Statistics and Stylized Facts

Description

Creates table showing statistics for the worst drawdowns.

Usage

table.Drawdowns(R, top = 5, digits = 4, geometric = TRUE, ...)

Arguments

R

an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns

top

the number of drawdowns to include

digits

number of digits to round results to

geometric

utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns, default TRUE

...

any other passthru parameters

Details

Returns an data frame with columns:

• From starting period, high water mark

• Trough period of low point

• To ending period, when initial high water mark is recovered

• Depth drawdown to trough (typically as percentage returns)

• Length length in periods

• toTrough number of periods to trough

• Recovery number of periods to recover

Author(s)

Peter Carl

References

Bacon, C. Practical Portfolio Performance Measurement and Attribution. Wiley. 2004. p. 88

See Also

DownsideDeviation
maxDrawdown
findDrawdowns
sortDrawdowns
chart.Drawdown
table.DownsideRisk

Examples

data(edhec)
table.Drawdowns(edhec[,1,drop=FALSE])
table.Drawdowns(edhec[,12,drop=FALSE])
data(managers)
table.Drawdowns(managers[,8,drop=FALSE])

result=table.Drawdowns(managers[,1,drop=FALSE])

# This was really nice before Hmisc messed up 'format' from R-base
#require("Hmisc")
#textplot(Hmisc::format.df(result, na.blank=TRUE, numeric.dollar=FALSE, 
#           cdec=c(rep(3,4), rep(0,3))), rmar = 0.8, cmar = 1.5,  
#           max.cex=.9, halign = "center", valign = "top", row.valign="center", 
#           wrap.rownames=5, wrap.colnames=10, mar = c(0,0,3,0)+0.1) 
# title(main="Largest Drawdowns for HAM1")