PMinCDaR: Portfolio optimisation for minimum conditional draw down at...

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Description

This function returns the result of a long-only portfolio optimization whereby the portfolio's (historic) conditional draw down at risk is minimized.

Usage

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PMinCDaR(PriceData, alpha = 0.95, softBudget = FALSE, ...)

Arguments

PriceData

A rectangular array of price data.

alpha

Numeric, the confidence level for which the conditional draw down shall be computed.

softBudget

Logical, whether the budget constraint shall be implemented as a soft constraint, i.e. the sum of the weights can be less than one. The default is to use an equality constraint.

...

Arguments are passed down to Rglpk_solve_LP

Details

This function implements a long-only portfolio optimisation for a minimum conditional draw down at risk (see references below). The problem can be stated in the form of a linear program and GLPK is used as solver.

Value

An object of formal class "PortAdd".

Note

A warning is issued in case the solver had exit status not equal to zero.

Author(s)

Bernhard Pfaff

References

Chekhlov, A. and Uryasev, S. and Zabarankin, M., Portfolio Optimization with Drawdown Constraints, Department of Industrial and Systems Engineering, University of Florida, Research Report 2000-5, 2000, Gainesville, FL. Chekhlov, A. and Uryasev, S. and Zabarankin, M., Drawdown Measure in Portfolio Optimization, International Journal of Theoretical and Applied Finance, 2005, 8(1), 13–58.

See Also

"PortSol", "PortCdd", "PortDD", PMaxDD, PAveDD, PCDaR

Examples

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## Not run: 
data(StockIndex)
popt <- PMinCDaR(PriceData = StockIndex, alpha = 0.95, softBudget = FALSE)

## End(Not run)

Example output

Loading required package: cccp
Loading required package: Rglpk
Loading required package: slam
Using the GLPK callable library version 4.52
Loading required package: timeSeries
Loading required package: timeDate
Financial Risk Modelling and Portfolio Optimisation with R (version 0.4-1)

FRAPO documentation built on May 2, 2019, 5:24 p.m.

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