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Construction of Stationary Time Series via the Giggs Sampler with Application to Volatility Models

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Author Info
Pitt, M.K.
Walker, S.G.
Abstract

In this paper, we provide a method for modeling stationary time series. We allow the family of marginal densities for the observations to be specified. Our approach is to construct the model with a specified marginal family and build the dependence structure around it. We show that the resulting time series is linear with a simple autocorrelation structure. In particular, we present an original application of the Gibbs sampler. We illustrate our approach by fitting a model to time series count data with a marginal Poisson-gamma density.

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File URL: http://www2.warwick.ac.uk/fac/soc/economics/research/workingpapers/publications/twerp595.pdf
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Paper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 595.

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Length: 30 pages
Date of creation: 2001
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Handle: RePEc:wrk:warwec:595

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Related research
Keywords: VOLATILITY ; TIME SERIES ; EXPECTATIONS;

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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  1. Michael K Pitt & Neil Shephard, . "Filtering via simulation: auxiliary particle filters," Economics Papers 1997-W13, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
  2. Ole Barndorff-Nielsen & Neil Shephard, 2000. "Non-Gaussian OU based models and some of their uses in financial economics," OFRC Working Papers Series 2000mf01, Oxford Financial Research Centre. [Downloadable!]
  3. Neil Shephard, 2005. "Stochastic Volatility," Economics Papers 2005-W17, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
  4. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August. [Downloadable!] (restricted)
  5. E. Gutiérrez-Peña & A. Smith & José Bernardo & Guido Consonni & Piero Veronese & E. George & F. Girón & M. Martínez & G. Letac & Carl Morris, 1997. "Exponential and bayesian conjugate families: Review and extensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 6(1), pages 1-90, June. [Downloadable!] (restricted)
  6. Praetz, Peter D, 1972. "The Distribution of Share Price Changes," Journal of Business, University of Chicago Press, vol. 45(1), pages 49-55, January. [Downloadable!] (restricted)
  7. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," Journal of Business, University of Chicago Press, vol. 47(2), pages 244-80, April. [Downloadable!] (restricted)
  8. He, Changli & Terasvirta, Timo, 1999. "Properties of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 92(1), pages 173-192, September. [Downloadable!] (restricted)
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  9. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-89, October.
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