We provide nonparametric methods for stochastic volatility modeling. Our methods allow for the joint evaluation of return and volatility dynamics with nonlinear drift and diffusion functions, nonlinear leverage effects, and jumps in returns and volatil- ity with possibly state-dependent jump intensities, among other features. In the first stage, we identify spot volatility by virtue of jump-robust nonparametric estimates. Using observed prices and estimated spot volatilities, the second stage extracts the functions and parameters driving price and volatility dynamics from nonparamet- ric estimates of the bivariate process’ infinitesimal moments. For these infinitesi- mal moment estimates, we report an asymptotic theory relying on joint in-fill and long-span arguments which yields consistency and weak convergence under mild assumptions.
|Titolo:||Nonparametric stochastic volatility|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||01.01 Articolo in Rivista|