MCMC interweaving strategy for estimating stochastic volatility model and its application
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Publication:6116260
DOI10.1080/03610918.2020.1861463OpenAlexW3114988358MaRDI QIDQ6116260
Publication date: 18 July 2023
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2020.1861463
Cites Work
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- Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models
- The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
- Volatility analysis with realized GARCH-Itô models
- Stochastic volatility with leverage: fast and efficient likelihood inference
- Simulation smoothing for state-space models: a computational efficiency analysis
- Quasi-maximum likelihood estimation of stochastic volatility models
- On functional limits of short- and long-memory linear processes with GARCH(1,1) noises
- Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
- Analytic Convergence Rates and Parameterization Issues for the Gibbs Sampler Applied to State Space Models
- Efficient parametrisations for normal linear mixed models
- Monte Carlo sampling methods using Markov chains and their applications
- Inference for the tail index of a GARCH(1,1) model and an AR(1) model with ARCH(1) errors
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