EstimatorSE {RPESE}

Wrapper Function for Standard Errors Estimates Functions

Description

EstimatorSE computes the standard error for specified risk and performance measures.

Usage

EstimatorSE(
  data,
  estimator.fun = c("DSR", "ES", "ESratio", "LPM", "Mean", "OmegaRatio", "RachevRatio",
    "robMean", "SD", "SemiSD", "SR", "SoR", "VaR", "VaRratio")[1],
  se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[1],
  cleanOutliers = FALSE,
  fitting.method = c("Exponential", "Gamma")[1],
  d.GLM.EN = 5,
  freq.include = c("All", "Decimate", "Truncate")[1],
  freq.par = 0.5,
  a = 0.3,
  b = 0.7,
  return.coef = FALSE,
  ...
)

Arguments

data

Data of returns for one or multiple assets or portfolios.

estimator.fun

Risk or performance measure to compute estimates of standard errors.

se.method

A character string indicating which method should be used to compute the standard error of the estimated standard deviation. One of: "IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor", or "none".

cleanOutliers

Boolean variable to indicate whether the pre-whitenning of the influence functions TS should be done through a robust filter. Default if FALSE.

fitting.method

Distribution used in the standard errors computation. Should be one of "Exponential" (default) or "Gamma".

d.GLM.EN

Order of the polynomial for the Exponential or Gamma fitting. Default polynomial order of 5.

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.

return.coef

Boolean variable to indicate whether the coefficients of the Exponential or Gamma fit are returned. Default is FALSE.

...

Additional parameters.

Value

A vector standard error estimates.

Author(s)

Xin Chen, [e-mail]

Anthony-Alexander Christidis, [e-mail]

Examples

# Loading data
data(edhec, package = "PerformanceAnalytics")
# Changing the data colnames
names(edhec) = c("CA", "CTA", "DIS", "EM", "EMN",
                 "ED", "FIA", "GM", "LS", "MA",
                 "RV", "SS", "FOF")
# Computing the standard errors for
# the three influence functions based approaches
EstimatorSE(edhec[,"CA"], se.method = c("IFcor"),
            cleanOutliers = FALSE,
            fitting.method = c("Exponential", "Gamma")[1])