Bayesian Inference on QGARCH Model Using the Adaptive Construction Scheme
AbstractWe study the performance of the adaptive construction scheme for a Bayesian inference on the Quadratic GARCH model which introduces the asymmetry in time series dynamics. In the adaptive construction scheme a proposal density in the Metropolis-Hastings algorithm is constructed adaptively by changing the parameters of the density to fit the posterior density. Using artificial QGARCH data we infer the QGARCH parameters by applying the adaptive construction scheme to the Bayesian inference of QGARCH model. We find that the adaptive construction scheme samples QGARCH parameters effectively, i.e. correlations between the sampled data are very small. We conclude that the adaptive construction scheme is an efficient method to the Bayesian estimation of the QGARCH model.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 0907.5276.
Date of creation: Jul 2009
Date of revision:
Publication status: Published in Eighth IEEE/ACIS International Conference on Computer and Information Science, (ICIS2009) 525-529
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-09-26 (All new papers)
- NEP-ECM-2009-09-26 (Econometrics)
- NEP-ETS-2009-09-26 (Econometric Time Series)
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- Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998.
"Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models,"
Review of Economic Studies,
Wiley Blackwell, vol. 65(3), pages 361-93, July.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, EconWPA.
- Tom Doan, . "KSCPOSTDRAW: RATS procedure to draw from posterior density needed in stochastic volatility model," Statistical Software Components RTS00101, Boston College Department of Economics.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, . "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- Tom Doan, . "RATS programs to replicate Jacquier, Polson, Rossi (1994) stochastic volatility," Statistical Software Components RTZ00105, Boston College Department of Economics.
- R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
- Tetsuya Takaishi, 2009. "Markov Chain Monte Carlo on Asymmetric GARCH Model Using the Adaptive Construction Scheme," Papers 0909.1478, arXiv.org.
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