NONPARAMETRIC ESTIMATION OF SECOND-ORDER STOCHASTIC DIFFERENTIAL EQUATIONS

DOI10.1017/S0266466607070375zbMath1237.62105OpenAlexW2009129315MaRDI QIDQ2886970

João Nicolau

Publication date: 14 May 2012

Published in: Econometric Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s0266466607070375

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items (15)

Local Linear Estimation of Second-order Jump-diffusion Model ⋮ Variance reduction approach for the volatility over a finite-time horizon ⋮ Re-weighted functional estimation of second-order diffusion processes ⋮ Non parametric bias reduction of diffusion coefficient in integrated diffusion processes ⋮ A test for a parametric form of the volatility in second-order diffusion models ⋮ Variance reduction estimation for return models with jumps using gamma asymmetric kernels ⋮ Adaptive nonparametric drift estimation of an integrated jump diffusion process ⋮ Estimation for a second-order jump diffusion model from discrete observations: application to stock market returns ⋮ Local linear estimator for stochastic differential equations driven by \(\alpha\)-stable Lévy motions ⋮ Consistency of a likelihood estimator for stochastic damping Hamiltonian systems. Totally observed data ⋮ Modeling financial time series through second-order stochastic differential equations ⋮ Local Linear Estimation of Second-Order Diffusion Models ⋮ Double-smoothed drift estimation of jump-diffusion model ⋮ Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps ⋮ Non Parametric Estimation of Second-Order Diffusion Equation by Using Asymmetric Kernels

Cites Work

• A hyperbolic diffusion model for stock prices
• Nonparametric estimation of scalar diffusions based on low frequency data
• Parameter estimation for a discrete sampling of an intergrated Ornstein-Uhlenbeck process
• Estimation of the coefficients of a diffusion from discrete observations
• Parameter Estimation for a Discretely Observed Integrated Diffusion Process
• Approximate discrete-time schemes for statistics of diffusion processes
• On estimating the diffusion coefficient from discrete observations
• Estimation of an Ergodic Diffusion from Discrete Observations
• Inference for Observations of Integrated Diffusion Processes
• Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes
• Fully Nonparametric Estimation of Scalar Diffusion Models
• Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-form Approximation Approach

This page was built for publication: NONPARAMETRIC ESTIMATION OF SECOND-ORDER STOCHASTIC DIFFERENTIAL EQUATIONS