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

  1 2 3 4 5 6 7 8 9 10 11 12 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.