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Indirect Estimation of Arfima and Varfima Models

Author

Listed:
  • 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.

Suggested Citation

  • Martin, V.L. & Wilkins, N.P., 1997. "Indirect Estimation of Arfima and Varfima Models," Department of Economics - Working Papers Series 547, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:547
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    References listed on IDEAS

    as
    1. 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.
    2. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 63-84, Suppl. De.
    3. Tauchen, George E., 1995. "New Minimum Chi-Square Methods in Empirical Finance," Working Papers 95-42, Duke University, Department of Economics.
    4. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
    5. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June.
    6. repec:crs:wpaper:9554 is not listed on IDEAS
    7. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    8. 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.
    9. 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.
    10. 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.
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    13. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    14. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(04), pages 657-681, October.
    15. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    16. 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.
    17. 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.
    18. 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.
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    Citations

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    Cited by:

    1. Pierre Perron & Rasmus T. Varneskov, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2011-050, Boston University - Department of Economics.
    2. Pai, Jeffrey & Ravishanker, Nalini, 2015. "Fast approximate likelihood evaluation for stable VARFIMA processes," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 160-168.
    3. Kristoufek, Ladislav, 2015. "On the interplay between short and long term memory in the power-law cross-correlations setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 218-222.
    4. 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.
    5. Nigel Wilkins, 2004. "Indirect Estimation of Long Memory Volatility Models," Econometric Society 2004 Far Eastern Meetings 459, Econometric Society.
    6. 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.
    7. 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.
    8. John Galbraith & Victoria Zinde-Walsh, 2001. "Autoregression-Based Estimators for ARFIMA Models," CIRANO Working Papers 2001s-11, CIRANO.
    9. Rebecca J. Sela & Clifford M. Hurvich, 2009. "Computationally efficient methods for two multivariate fractionally integrated models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 631-651, November.
    10. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2016. "Stock and currency market linkages: New evidence from realized spillovers in higher moments," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 167-185.
    11. repec:eee:ecofin:v:42:y:2017:i:c:p:393-420 is not listed on IDEAS

    More about this item

    Keywords

    ECONOMETRICS; EVALUATION;

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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