| Type: | Package |
| Title: | Estimates of Standard Errors for Risk and Performance Measures |
| Version: | 1.2.5 |
| Date: | 2022-09-07 |
| Author: | Anthony Christidis <anthony.christidis@stat.ubc.ca>, Xin Chen <chenx26@uw.edu> |
| Maintainer: | Anthony Christidis <anthony.christidis@stat.ubc.ca> |
| Description: | Estimates of standard errors of popular risk and performance measures for asset or portfolio returns using methods as described in Chen and Martin (2021) <doi:10.21314/JOR.2020.446>. |
| Biarch: | true |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Imports: | xts, zoo, boot, RPEIF, RPEGLMEN, RobStatTM |
| Suggests: | testthat, R.rsp, PerformanceAnalytics |
| RoxygenNote: | 7.2.1 |
| VignetteBuilder: | R.rsp |
| NeedsCompilation: | no |
| Packaged: | 2022-09-08 07:05:56 UTC; antho |
| Repository: | CRAN |
| Date/Publication: | 2022-09-08 07:22:55 UTC |
Standard Error Estimate for Downside Sharpe Ratio (DSR) of Returns
Description
DSR.SE computes the standard error of the downside Sharpe ratio of the returns.
Usage
DSR.SE(
data,
rf = 0,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
rf |
Risk free rate. |
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
DSR.SE(edhec, se.method = c("IFiid","IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Expected Shortfall (ES) of Returns
Description
ES.SE computes the standard error of the expected shortfall of the returns.
Usage
ES.SE(
data,
p = 0.95,
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. |
p |
Confidence level for calculation. Default value is p = 0.95. |
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)
Xin Chen, chenx26@uw.edu
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
ES.SE(edhec, se.method = c("IFiid","IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Expected Shortfall Ratio (ESratio) of Returns
Description
ESratio.SE computes the standard error of the expected shortfall ratio of the returns.
Usage
ESratio.SE(
data,
alpha = 0.1,
rf = 0,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
alpha |
Lower tail probability. |
rf |
Risk-free interest rate. |
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
ESratio.SE(edhec, se.method=c("IFiid","IFcorAdapt"),
cleanOutliers=FALSE,
fitting.method=c("Exponential", "Gamma")[1])
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:
|
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. |
Value
A vector standard error estimates.
Author(s)
Xin Chen, chenx26@uw.edu
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 three influence functions based approaches
EstimatorSE(edhec[,"CA"], se.method = c("IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Lower Partial Moment (LPM) of Returns
Description
LPM.SE computes the standard error of the LPM of the returns.
Usage
LPM.SE(
data,
const = 0,
order = 1,
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. |
const |
Constant threshold. |
order |
Order for the lower partial moment (should be 1 or 2). |
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)
Xin Chen, chenx26@uw.edu
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
LPM.SE(edhec, se.method = c("IFiid","IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Mean of Returns
Description
Mean.SE computes the standard error of the mean of the returns.
Usage
Mean.SE(
data,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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
Mean.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Omega Ratio of Returns
Description
OmegaRatio.SE computes the standard error of the Omega ratio of the returns.
Usage
OmegaRatio.SE(
data,
const = 0,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
const |
Constant threshold. |
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
OmegaRatio.SE(edhec, se.method = c("IFiid","IFcorAdapt")[1],
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Rachev Ratio of Returns
Description
RachevRatio.SE computes the standard error of the Rachev ratio of the returns.
Usage
RachevRatio.SE(
data,
alpha = 0.1,
beta = 0.1,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
alpha |
Lower tail probability. |
beta |
Upper tail probability. |
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
RachevRatio.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Standard Deviation (SD) of Returns
Description
SD.SE computes the standard error of the standard deviation of the returns.
Usage
SD.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
SD.SE(edhec, se.method = c("IFiid","IFcor","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Sharpe Ratio (SR) of Returns
Description
SR.SE computes the standard error of the Sharpe ratio of the returns.
Usage
SR.SE(
data,
rf = 0,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
rf |
Risk free rate. |
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
SR.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
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])
Standard Error Estimate for Sortino Ratio (SoR) of Returns
Description
SoR.SE computes the standard error of the Sortino ratio of the returns.
Usage
SoR.SE(
data,
const = 0,
threshold = c("mean", "const")[1],
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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")[1],
return.coef = FALSE,
...
)
Arguments
data |
Data of returns for one or multiple assets or portfolios. |
const |
Minimum acceptable return for threshold. |
threshold |
Parameter to determine whether we use a "mean" or "const" threshold. |
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
SoR.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Value-at-Risk (VaR) of Returns
Description
VaR.SE computes the standard error of the value-at-risk of the returns.
Usage
VaR.SE(
data = NULL,
alpha = 0.95,
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. |
alpha |
Confidence level for calculation. Default is alpha=0.95. |
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
VaR.SE(edhec, se.method = c("IFiid","IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Standard Error Estimate for Value-at-Risk Ratio (VaRratio) of Returns
Description
VaRratio.SE computes the standard error of the value-at-risk ratio of the returns.
Usage
VaRratio.SE(
data,
alpha = 0.1,
rf = 0,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
alpha |
The tail probability of interest. |
rf |
Risk-free interest rate. |
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
VaRratio.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
Formatted Output for Standard Errors Functions in RPESE
Description
printSE returns a formatted output from standard error functions from RPESE.
Usage
printSE(SE.data, round.digit = 3, round.out = TRUE)
Arguments
SE.data |
Standard error estimates output from RPESE functions. |
round.digit |
Number of digits for rounding. |
round.out |
Round data (TRUE) with round.digit number of digits. Default is TRUE. |
Value
A data frame with formatted output from standard error functions from RPESE.
Author(s)
Xin Chen, chenx26@uw.edu
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
ES.out <- ES.SE(edhec, se.method = c("IFiid","IFcor"),
cleanOutliers = FALSE,
fitting.method = c("Exponential", "Gamma")[1])
# Print the output
printSE(ES.out)
Standard Error Estimate for Robust Location (Mean) M-Estimator of Returns
Description
robMean.SE computes the standard error of the robust location (mean) M-estimator of the returns.
Usage
robMean.SE(
data,
family = c("mopt", "opt", "bisquare")[1],
eff = 0.95,
se.method = c("IFiid", "IFcor", "IFcorAdapt", "IFcorPW", "BOOTiid", "BOOTcor")[c(1, 4)],
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. |
family |
Family for robust m-estimator of location. Must be one of "mopt" (default), "opt" or "bisquare". |
eff |
Tuning parameter for the normal distribution efficiency. Default is 0.99. |
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
robMean.SE(edhec, se.method = c("IFiid","IFcorAdapt"),
fitting.method = c("Exponential", "Gamma")[1],
family = "mopt", eff = 0.95)