Bayesian estimation and inference for log-ACD models
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Publication:736572
DOI10.1007/s00180-015-0576-8zbMath1342.65033OpenAlexW2082182397MaRDI QIDQ736572
Edward M. H. Lin, Richard H. Gerlach, M. Shelton Peiris
Publication date: 4 August 2016
Published in: Computational Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00180-015-0576-8
Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)
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Uses Software
Cites Work
- A family of autoregressive conditional duration models
- On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks
- Finite sample properties of the QMLE for the log-ACD model: application to Australian stocks
- Bayesian analysis of the stochastic conditional duration model
- Volatility forecasting using threshold heteroskedastic models of the intra-day range
- Nonparametric regression using Bayesian variable selection
- Generalized autoregressive conditional heteroscedasticity
- The stochastic conditional duration model: a latent variable model for the analysis of financial durations
- Autoregressive Conditional Density Estimation
- Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
- A nonlinear autoregressive conditional duration model with applications to financial transaction data
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