Nonparametric estimation for a stochastic volatility model

Details Nonparametric estimation for a stochastic volatility model Nonparametric estimation for a stochastic volatility model

2007-12-21

arxiv.org/abs/0712.3735v1

Statistics

Methodology

Scientific paper

Consider discrete time observations (X_{\ell\delta})_{1\leq \ell \leq n+1}$ of the process $X$ satisfying $dX_t= \sqrt{V_t} dB_t$, with $V_t$ a one-dimensional positive diffusion process independent of the Brownian motion $B$. For both the drift and the diffusion coefficient of the unobserved diffusion $V$, we propose nonparametric least square estimators, and provide bounds for theirrisk. Estimators are chosen among a collection of functions belonging to a finite dimensional space whose dimension is selected by a data driven procedure. Implementation on simulated data illustrates how the method works.

Affiliated with

Also associated with

No associations

Rating

Nonparametric estimation for a stochastic volatility model does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Nonparametric estimation for a stochastic volatility model, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nonparametric estimation for a stochastic volatility model will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-697006