Volatility forecasting using threshold heteroskedastic models of the intra-day range

DOI10.1016/j.csda.2007.08.002zbMath1452.62748OpenAlexW1985831857MaRDI QIDQ1023630

Edward M. H. Lin, Cathy W. S. Chen, Richard H. Gerlach

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.08.002

zbMATH Keywords

MCMC methodsvolatility modelBayes inferenceconditional autoregressive range (CARR) modelsize and sign asymmetrythreshold variable

Mathematics Subject Classification ID

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)

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Uses Software

• FinTS

Cites Work

• Unobserved component models with asymmetric conditional variances
• Comparison of nonnested asymmetric heteroskedastic models
• Regime-switching Pareto distributions for ACD models
• Generalized autoregressive conditional heteroscedasticity
• Markov chains for exploring posterior distributions. (With discussion)
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Modeling the Asymmetry of Stock Movements Using Price Ranges
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• On Gibbs sampling for state space models
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• BAYESIAN INFERENCE OF THRESHOLD AUTOREGRESSIVE MODELS
• Quadratic ARCH Models
• Equation of State Calculations by Fast Computing Machines
• ASSESSING AND TESTING FOR THRESHOLD NONLINEARITY IN STOCK RETURNS
• Monte Carlo sampling methods using Markov chains and their applications
• Analysis of Financial Time Series

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