Description Usage Arguments Details Value References
WDKLL estimator of CVaR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | wdkll_cvar(
formula,
data,
prob = 0.95,
nw_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
nw_h,
pdf_kernel = c("Gaussian", "Epanechinikov", "Tricube", "Boxcar"),
h0,
init = 0,
eps = 1e-05,
iter = 1000,
lower_invert = -3,
upper_invert = 3
)
|
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 |
pdf_kernel |
Kernel for initial estimate of conditinal pdf |
h0 |
Bandwidth for pdf kernel |
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 |
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)
CVaR given x
Cai, Z., & Wang, X. (2008). Nonparametric estimation of conditional VaR and expected shortfall. Journal of Econometrics, 147(1), 120-130.
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