For some confidence level \(p\), the conditional drawdown is the the mean of the worst \(p\%\) drawdowns.
CDD(R, weights = NULL, geometric = TRUE, invert = TRUE, p = 0.95, ...)
| R | an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns |
|---|---|
| weights | portfolio weighting vector, default NULL, see Details |
| geometric | utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns, default TRUE |
| invert | TRUE/FALSE whether to invert the drawdown measure. see Details. |
| p | confidence level for calculation, default p=0.95 |
| … | any other passthru parameters |
Chekhlov, A., Uryasev, S., and M. Zabarankin. Portfolio Optimization With Drawdown Constraints. B. Scherer (Ed.) Asset and Liability Management Tools, Risk Books, London, 2003 http://www.ise.ufl.edu/uryasev/drawdown.pdf
data(edhec) t(round(CDD(edhec),4))#> Conditional Drawdown 5% #> Convertible Arbitrage 0.0927 #> CTA Global 0.0548 #> Distressed Securities 0.0695 #> Emerging Markets 0.3433 #> Equity Market Neutral 0.0111 #> Event Driven 0.0813 #> Fixed Income Arbitrage 0.1086 #> Global Macro 0.0407 #> Long/Short Equity 0.0842 #> Merger Arbitrage 0.0527 #> Relative Value 0.0439 #> Short Selling 0.4293 #> Funds of Funds 0.0563