wnw_cvar: Weighted Double Kernel Local Linear Estimation of Conditional...

In ygeunkim/ceshat: Nonparametric Estimation of Conditional Expected Shortfall

Description

WDKLL estimator of CVaR

Usage

wnw_cvar(
  formula,
  data,
  prob = 0.95,
  nw_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
  nw_h,
  init = 0,
  eps = 1e-05,
  iter = 1000,
  lower_invert = -3,
  upper_invert = 3
)

Arguments

formula	an object class formula.
data	an optional data to be used.
prob	upper tail probability for VaR
nw_kernel	Kernel for weighted nadaraya watson
nw_h	Bandwidth for WNW
init	initial value for finding lambda
eps	small value
iter	maximum iteration when finding lambda
lower_invert	lower y when inverting the cdf
upper_invert	upper y when inverting the cdf

Details

CVaR can be earned by inverting the CDF.

\hat{nu}_p(x) = \hat{S}_c^{-1}(p \mid x)

where

\hat{S}(y \mid x)_c(y \mid x) = 1 - \hat{F}_c(y \mid x)

Value

CVaR given x

References

Cai, Z., & Wang, X. (2008). Nonparametric estimation of conditional VaR and expected shortfall. Journal of Econometrics, 147(1), 120-130.

ygeunkim/ceshat documentation built on Dec. 16, 2019, 12:39 p.m.