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Indirect Estimation of Arfima and Varfima Models

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Author Info

  • Martin, V.L.
  • Wilkins, N.P.

Abstract

Indirect estimation methods are proposed for estimating univariate ARFIMA , as well as more complex multivariate VARFIMA models. Special attention is given to comparing the finite sampling properties of the indirect estimator with Sowell's (1992a) exact time domain maximum likelihood estimator and the Geweke and Porter-Hudak (1983) spectral regression estimator.

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Bibliographic Info

Paper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 547.

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Length: 38 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:mlb:wpaper:547

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Postal: Department of Economics, The University of Melbourne, 5th Floor, Economics and Commerce Building, Victoria, 3010, Australia
Phone: +61 3 8344 5289
Fax: +61 3 8344 6899
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Web page: http://www.economics.unimelb.edu.au
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Keywords: ECONOMETRICS; EVALUATION;

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References

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  1. Gary Koop, 1995. "Bayesian Analysis of Long Memory and Persistence using ARFIMA Models," Working Papers gkoop-95-01, University of Toronto, Department of Economics.
  2. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
  3. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
  4. repec:fth:inseep:9554 is not listed on IDEAS
  5. Pagan, A.R. & Hall, A.D. & Martin, V., 1995. "Modelling the Term Structure," Papers 284, Australian National University - Department of Economics.
  6. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(04), pages 657-681, October.
  7. Yin-Wong Cheung & Francis X. Diebold, 1990. "On maximum-likelihood estimation of the differencing parameter of fractionally integrated noise with unknown mean," Discussion Paper / Institute for Empirical Macroeconomics 34, Federal Reserve Bank of Minneapolis.
  8. Pagan, A.R., 1996. "Simulation Based Estimation of Some Factor Models in Econometrics," Department of Economics - Working Papers Series 521, The University of Melbourne.
  9. Chung, Ching-Fan & Baillie, Richard T, 1993. "Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models," Empirical Economics, Springer, vol. 18(4), pages 791-806.
  10. Ming Liu & Harold Zhang, 1996. "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," GSIA Working Papers 34, Carnegie Mellon University, Tepper School of Business.
  11. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
  12. Chung, Ching-Fan, 1994. "A note on calculating the autocovariances of the fractionally integrated ARMA models," Economics Letters, Elsevier, vol. 45(3), pages 293-297.
  13. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
  14. Tieslau, Margie A. & Schmidt, Peter & Baillie, Richard T., 1996. "A minimum distance estimator for long-memory processes," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 249-264.
  15. Tauchen, George E., 1995. "New Minimum Chi-Square Methods in Empirical Finance," Working Papers 95-42, Duke University, Department of Economics.
  16. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
  17. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  18. Hosoya, Yuzo, 1996. "The quasi-likelihood approach to statistical inference on multiple time-series with long-range dependence," Journal of Econometrics, Elsevier, vol. 73(1), pages 217-236, July.
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Citations

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Cited by:
  1. Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, School of Economics and Management, University of Aarhus.
  2. Pai, Jeffrey & Ravishanker, Nalini, 2009. "Maximum likelihood estimation in vector long memory processes via EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4133-4142, October.
  3. John Galbraith & Victoria Zinde-Walsh, 2001. "Autoregression-Based Estimators for ARFIMA Models," CIRANO Working Papers 2001s-11, CIRANO.
  4. Nigel Wilkins, 2004. "Indirect Estimation of Long Memory Volatility Models," Econometric Society 2004 Far Eastern Meetings 459, Econometric Society.
  5. D. S. Poskitt, 2005. "Autoregressive Approximation in Nonstandard Situations: The Non-Invertible and Fractionally Integrated Cases," Monash Econometrics and Business Statistics Working Papers 16/05, Monash University, Department of Econometrics and Business Statistics.
  6. Ellis, Craig & Wilson, Patrick, 2004. "Another look at the forecast performance of ARFIMA models," International Review of Financial Analysis, Elsevier, vol. 13(1), pages 63-81.

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