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CDD

Calculate Uryasev's proposed Conditional Drawdown at Risk (CDD or CDaR) measure


Description

For some confidence level p, the conditional drawdown is the the mean of the worst p\% drawdowns.

Usage

CDD(R, weights = NULL, geometric = TRUE, invert = TRUE, p = 0.95, ...)

Arguments

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

Author(s)

Brian G. Peterson

References

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

See Also

Examples

data(edhec)
t(round(CDD(edhec),4))

PerformanceAnalytics

Econometric Tools for Performance and Risk Analysis

v2.0.4
GPL-2 | GPL-3
Authors
Brian G. Peterson [cre, aut, cph], Peter Carl [aut, cph], Kris Boudt [ctb, cph], Ross Bennett [ctb], Joshua Ulrich [ctb], Eric Zivot [ctb], Dries Cornilly [ctb], Eric Hung [ctb], Matthieu Lestel [ctb], Kyle Balkissoon [ctb], Diethelm Wuertz [ctb], Anthony Alexander Christidis [ctb], R. Douglas Martin [ctb], Zeheng 'Zenith' Zhou [ctb], Justin M. Shea [ctb]
Initial release
2020-02-05

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