| SemiSD.SE {RPESE} | R Documentation | 
Standard Error Estimate for Semi-Standared Deviation (SemiSD) of Returns
Description
SemiSD.SE computes the standard error of the SSD of the returns.
Usage
SemiSD.SE(
  data,
  se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[1:2],
  cleanOutliers = FALSE,
  fitting.method = c("Exponential", "Gamma")[1],
  d.GLM.EN = 5,
  freq.include = c("All", "Decimate", "Truncate")[1],
  freq.par = 0.5,
  corOut = c("none", "retCor", "retIFCor", "retIFCorPW")[1],
  return.coef = FALSE,
  ...
)
Arguments
| data | Data of returns for one or multiple assets or portfolios. | 
| 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:
 | 
| 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  | 
| corOut | Return correlation of the returns or the influence function transformed returns. Must be one of "retCor", "retIFCor" or "none" (default). | 
| return.coef | Boolean variable to indicate whether the coefficients of the penalized GLM fit are returned. Default if FALSE. | 
| ... | Additional parameters. | 
Value
A vector or a list depending on se.method.
Author(s)
Anthony-Alexander Christidis, anthony.christidis@stat.ubc.ca
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 two influence functions based approaches
SemiSD.SE(edhec, se.method = c("IFiid","IFcor"),
          cleanOutliers = FALSE,
          fitting.method = c("Exponential", "Gamma")[1])