Maximum likelihood estimation of partially observed diffusion models
From MaRDI portal
Publication:469573
DOI10.1016/j.jeconom.2014.02.002zbMath1298.62143OpenAlexW1998322595MaRDI QIDQ469573
Jun Yu, Tore Selland Kleppe, Hans Julius Skaug
Publication date: 11 November 2014
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://ink.library.smu.edu.sg/soe_research/1797
Point estimation (62F10) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60)
Related Items
WEAK DIFFUSION LIMITS OF DYNAMIC CONDITIONAL CORRELATION MODELS ⋮ Maximum likelihood estimation of latent Markov models using closed-form approximations
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Pricing of Options and Corporate Liabilities
- On leverage in a stochastic volatility model
- Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models
- Saddlepoint approximations for continuous-time Markov processes
- Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese yuan
- Efficient high-dimensional importance sampling
- Testing the assumptions behind importance sampling
- Estimating the structural credit risk model when equity prices are contaminated by trading noises
- A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions
- Bayesian analysis of structural credit risk models with microstructure noises
- A semiparametric stochastic volatility model
- Quasi-maximum likelihood estimation of stochastic volatility models
- Generalized autoregressive conditional heteroscedasticity
- Closed-form likelihood expansions for multivariate diffusions
- ARCH models as diffusion approximations
- Simulated maximum likelihood estimation of continuous time stochastic volatility models
- Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers
- Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance
- A Method of Second-Order Accuracy Integration of Stochastic Differential Equations
- Estimation for nonlinear stochastic differential equations by a local linearization method1
- A YIELD‐FACTOR MODEL OF INTEREST RATES
- Numerical Optimization
- Multivariate Stochastic Variance Models
- Likelihood analysis of non-Gaussian measurement time series
- Monte Carlo maximum likelihood estimation for non-Gaussian state space models
- Transform Analysis and Asset Pricing for Affine Jump-diffusions
- Likelihood Inference for Discretely Observed Nonlinear Diffusions
- Bayesian Inference in Econometric Models Using Monte Carlo Integration
- A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
- Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-form Approximation Approach
- Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models
- Nonrecursive Models as Discrete Approximations to Systems of Stochastic Differential Equations
