Parsimony inducing priors for large scale state-space models
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Publication:2155306
DOI10.1016/j.jeconom.2021.11.005OpenAlexW3129837527MaRDI QIDQ2155306
Ruey S. Tsay, Robert E. McCulloch, Hedibert Freitas Lopes
Publication date: 15 July 2022
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2021.11.005
parallel computingshrinkagesparsityBayesian modelingconditional heteroscedasticityforward filtering and backward sampling
Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
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Cites Work
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- Achieving shrinkage in a time-varying parameter model framework
- Sparse Bayesian time-varying covariance estimation in many dimensions
- Analysis of high dimensional multivariate stochastic volatility models
- The structure of dynamic correlations in multivariate stochastic volatility models
- Cholesky-GARCH models with applications to finance
- Bayesian thinking, modeling and computation.
- Factor stochastic volatility with time varying loadings and Markov switching regimes
- On singular Wishart and singular multivariate beta distributions
- Dynamic variable selection with spike-and-slab process priors
- Multivariate stochastic volatility with Bayesian dynamic linear models
- Sparse estimation of large covariance matrices via a nested Lasso penalty
- Time-varying sparsity in dynamic regression models
- Stochastic model specification search for Gaussian and partial non-Gaussian state space models
- Inference with normal-gamma prior distributions in regression problems
- A new approach to Cholesky-based covariance regularization in high dimensions
- Nonparametric estimation of large covariance matrices of longitudinal data
- Forward adaptive banding for estimating large covariance matrices
- Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
- Multivariate Stochastic Variance Models
- Bayesian Vector Autoregressions with Stochastic Volatility
- On the Long-Run Volatility of Stocks
- Dynamic dependence networks: Financial time series forecasting and portfolio decisions
- Hierarchical Shrinkage in Time‐Varying Parameter Models
- Dynamic Shrinkage Processes
- High‐Dimensional Covariance Estimation
- Handbook of Volatility Models and Their Applications
- Multivariate Stochastic Volatility: A Review
- Factor Multivariate Stochastic Volatility via Wishart Processes
- Covariance matrix selection and estimation via penalised normal likelihood
- Time Varying Structural Vector Autoregressions and Monetary Policy
- Stochastic Model Specification Search for Time-Varying Parameter VARs