Bayesian estimation of Gegenbauer long memory processes with stochastic volatility: methods and applications
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Publication:2691760
DOI10.1515/snde-2015-0110OpenAlexW2794406212MaRDI QIDQ2691760
M. Shelton Peiris, Andrew Phillip, Jennifer So-Kuen Chan
Publication date: 30 March 2023
Published in: Studies in Nonlinear Dynamics and Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/snde-2015-0110
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)
Related Items (2)
Bayesian estimation of Gegenbauer processes ⋮ Estimation methods for stationary Gegenbauer processes
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Cites Work
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- An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series
- Stochastic volatility with leverage: fast and efficient likelihood inference
- Bayesian analysis of stochastic volatility models with fat-tails and correlated errors
- Estimation of seasonal fractionally integrated processes
- Data analysis using regression models with missing observations and long-memory: an application study
- Generalised long-memory GARCH models for intra-daily volatility
- Fractionally integrated generalized autoregressive conditional heteroskedasticity
- Long memory relationships and the aggregation of dynamic models
- Fractional integration analysis of long-run behavior for US macroeconomic time series
- Bayes inference in regression models with ARMA\((p,q)\) errors
- Weak convergence and optimal scaling of random walk Metropolis algorithms
- Optimal scaling for various Metropolis-Hastings algorithms.
- Seasonal FIEGARCH processes
- Long memory with stochastic variance model: a recursive analysis for US inflation
- Infinite-order, long-memory heterogeneous autoregressive models
- State space modeling of Gegenbauer processes with long memory
- State space modeling of long-memory processes
- Moving average stochastic volatility models with application to inflation forecast
- Testing for long memory in the presence of non-linear deterministic trends with Chebyshev polynomials
- Handbook of Monte Carlo Methods
- THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
- The Long Memory of the Efficient Market
- Dual Long Memory in Inflation Dynamics across Countries of the Euro Area and the Link between Inflation Uncertainty and Macroeconomic Performance
- Fractional differencing
- AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
- ON GENERALIZED FRACTIONAL PROCESSES
- Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
- Bayes Factors
- Modelling stochastic volatility using generalizedtdistribution
- Fractional Brownian Motions, Fractional Noises and Applications
- Long-Run Linearity, Locally Gaussian Process, H-Spectra and Infinite Variances
- Regimes and long memory in realized volatility
- Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
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