Controls Function for the Computation of Standard Errors for Risk and Performance estimators

RPESE.controls sets the different control parameters used in the compuation of standard errors for risk and performance estimators.

Usage

RPESE.control(
  estimator = c("Mean", "SD", "VaR", "ES", "SR", "DSR", "SoR", "ESratio", "VaRratio",
    "SoR", "LPM", "OmegaRatio", "SemiSD", "RachevRatio")[1],
  se.method = NULL,
  cleanOutliers = NULL,
  fitting.method = NULL,
  freq.include = NULL,
  freq.par = NULL,
  a = NULL,
  b = NULL
)

Arguments

estimator: Risk or performance estimator used to set default control parameters. Default is "Mean" estimator.
se.method: A character string indicating which method should be used to compute the standard error of the estimated standard deviation. One or a combination of: "IFiid" (default), "IFcor" (default), "IFcorPW", "IFcorAdapt", "BOOTiid" or "BOOTcor".
cleanOutliers: Boolean variable to indicate whether the pre-whitenning of the influence functions TS should be done through a robust filter.
fitting.method: Distribution used in the standard errors computation. Should be one of "Exponential" (default) or "Gamma".
freq.include: Frequency domain inclusion criteria. Must be one of "All" (default), "Decimate" or "Truncate."
freq.par: Percentage of the frequency used if "freq.include" is "Decimate" or "Truncate." Default is 0.5.
a: First adaptive method parameter.
b: Second adaptive method parameter.

Value

A list of different control parameters for the computation of standard errors.

Author

Anthony-Alexander Christidis, [email protected]

Examples

# Case where we want the default parameters for the ES
ES.control <- RPESE.control(estimator="ES")
# Case where we also set additional parameters manually
ES.control.2 <- RPESE.control(estimator="ES", se.method=c("IFcor", "BOOTiid"),
                              cleanOutliers=TRUE, freq.include="Decimate")
# These lists can be passed onto the functions (e.g., ES) to control the parameters
# for computing and returning standard errors.