Showing 1 - 6 of 6
with a penalization approach yielding sparsity and reducing model complexity. Small sample properties of the estimator are …
Persistent link: https://www.econbiz.de/10010331130
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...
Persistent link: https://www.econbiz.de/10010270724
Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...
Persistent link: https://www.econbiz.de/10010270732
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a...
Persistent link: https://www.econbiz.de/10010270813
Let (X1, Y1), ..., (Xn, Yn) be i.i.d. rvs and let v(x) be the unknown T-expectile regression curve of Y conditional on X. An expectile-smoother vn(x) is a localized, nonlinear estimator of v(x). The strong uniform consistency rate is established under general conditions. In many applications it...
Persistent link: https://www.econbiz.de/10010281559
properties of the estimators, especially the L2 convergence rate, the sparsity, and the oracle property. Simulation studies and a …
Persistent link: https://www.econbiz.de/10010318744