Inference methods for discretely observed continuous-time stochastic volatility models: A commented overview
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Publication:862564
DOI10.1007/s10690-006-9015-8zbMath1134.91430OpenAlexW1989524222MaRDI QIDQ862564
Tohru Ozaki, R. J. Biscay, J. C. Jimenez
Publication date: 24 January 2007
Published in: Asia-Pacific Financial Markets (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10690-006-9015-8
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Cites Work
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- Large Sample Properties of Generalized Method of Moments Estimators
- The Pricing of Options and Corporate Liabilities
- A statistical comparison of the short-term interest rate models for Japan, U.S., and Germany
- Estimation for diffusion processes from discrete observation
- Estimating equations based on eigenfunctions for a discretely observed diffusion process
- Estimating continuous-time stochastic volatility models of the short-term interest rate
- Quasi-likelihood and its application. A general approach to optimal parameter estimation
- A hyperbolic diffusion model for stock prices
- Applying the EKF to stochastic differential equations with level effects
- Adaptive estimation in diffusion processes.
- Maximum likelihood estimation of time-inhomogeneous diffusions.
- Martingale estimation functions for discretely observed diffusion processes
- Consistency and asymptotic normality of an approximate maximum likelihood estimator for discretely observed diffusion processes
- Parameter estimation for discretely observed stochastic volatility models
- Asymptotic normality of the maximum likelihood estimator in state space models
- Stochastic processes and filtering theory
- A nonparametric method of estimating nonlinear dynamical system models
- Prediction‐based estimating functions
- Simplified Estimating Functions for Diffusion Models with a High‐dimensional Parameter
- Discretely Observed Diffusions: Approximation of the Continuous‐time Score Function
- Discretely Observed Diffusions: Classes of Estimating Functions and Small Δ‐optimality
- The Role of the Likelihood Function in the Estimation of Chaos Models
- On inference for partially observed nonlinear diffusion models using the Metropolis-Hastings algorithm
- A Theory of the Term Structure of Interest Rates
- An innovation approach to non-Gaussian time series analysis
- Asymptotic theory for non-linear least squares estimator for diffusion processes
- An Approximate Innovation Method For The Estimation Of Diffusion Processes From Discrete Data
- Approximate discrete-time schemes for statistics of diffusion processes
- ESTIMATION IN CONTINUOUS-TIME STOCHASTIC VOLATILITY MODELS USING NONLINEAR FILTERS
- Reprojecting Partially Observed Systems with Application to Interest Rate Diffusions
- Miscellanea. A statistical method of estimation and simulation for systems of stochastic differential equations
- Some aspects of recursive parameter estimation
- Recursive Estimation in Diffusion Model
- Identification of Nonstationary Diffusion Model by the Method of Sieves
- Nonparametric Identification for Diffusion Processes
- Asymptotic Statistics
- ESTIMATION OF CONTINUOUS-TIME MODELS FOR STOCK RETURNS AND INTEREST RATES
- CONTINUOUS-TIME DYNAMICAL SYSTEMS WITH SAMPLED DATA, ERRORS OF MEASUREMENT AND UNOBSERVED COMPONENTS
- On estimating the diffusion coefficient from discrete observations
- Estimation of an Ergodic Diffusion from Discrete Observations
- Estimation of Diffusion Processes by Simulated Moment Methods
- Comparative study of estimation methods for continuous time stochastic processes
- Nonparametric state estimation of diffusion processes
- On the efficacy of simulated maximum likelihood for estimating the parameters of stochastic differential Equations*
- Computational Aspects Related to Martingale Estimating Functions for a Discretely Observed Diffusion
- A Reexamination of Diffusion Estimators With Applications to Financial Model Validation
- Likelihood Inference for Discretely Observed Nonlinear Diffusions
- Local linearization filters for non-linear continuous-discrete state space models with multiplicative noise
- Simulated Likelihood Approximations for Stochastic Volatility Models
- Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes
- Nonparametric Pricing of Interest Rate Derivative Securities
- A comparative study of maximum likelihood estimators for nonlinear dynamical system models
- Simple and Explicit Estimating Functions for a Discretely Observed Diffusion Process
- Non‐parametric Kernel Estimation of the Coefficient of a Diffusion
- Evaluation of likelihood functions for Gaussian signals
- Portfolio Analysis in a Stable Paretian Market
- A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
- Stock Price Distributions with Stochastic Volatility: An Analytic Approach
- Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-form Approximation Approach
- Stochastic volatility models as hidden Markov models and statistical applications
- The Monte-Carlo method for filtering with discrete-time observations
