EstimatorSE | R Documentation |
EstimatorSE
computes the standard error for specified risk and performance measures.
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, ... )
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:
|
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 |
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. |
A vector standard error estimates.
Xin Chen, chenx26@uw.edu
Anthony-Alexander Christidis, anthony.christidis@stat.ubc.ca
# 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])
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