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Another look at the forecast performance of ARFIMA models

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  • Ellis, Craig
  • Wilson, Patrick

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  • 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.
    • Handle: RePEc:eee:finana:v:13:y:2004:i:1:p:63-81
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    1. John T. Barkoulas & Christopher F. Baum, 1997. "Fractional Differencing Modeling And Forecasting Of Eurocurrency Deposit Rates," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 20(3), pages 355-372, September.
    2. Barkoulas, John T & Labys, Walter C & Onochie, Joseph I, 1999. "Long Memory In Futures Prices," The Financial Review, Eastern Finance Association, vol. 34(1), pages 91-100, February.
    3. Cheung, Yin-Wong, 1993. "Long Memory in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 93-101, January.
    4. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    5. 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.
    6. John Okunev & Patrick J. Wilson, 1997. "Using Nonlinear Tests to Examine Integration Between Real Estate and Stock Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 25(3), pages 487-503, September.
    7. Andersson, Michael K., 1998. "On the Effects of Imposing or Ignoring Long Memory when Forecasting," SSE/EFI Working Paper Series in Economics and Finance 225, Stockholm School of Economics.
    8. Martin, Vance L. & Wilkins, Nigel P., 1999. "Indirect estimation of ARFIMA and VARFIMA models," Journal of Econometrics, Elsevier, vol. 93(1), pages 149-175, November.
    9. Smith, Jeremy & Yadav, Sanjay, 1994. "Forecasting costs incurred from unit differencing fractionally integrated processes," International Journal of Forecasting, Elsevier, vol. 10(4), pages 507-514, December.
    10. Brent W. Ambrose & Esther Ancel & Mark D. Griffiths, 1992. "The Fractal Structure of Real Estate Investment Trust Returns: The Search for Evidence of Market Segmentation and Nonlinear Dependency," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(1), pages 25-54, March.
    11. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    12. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    13. Ellis, Craig, 1999. "Estimation of the ARFIMA (p, d, q) fractional differencing parameter (d) using the classical rescaled adjusted range technique," International Review of Financial Analysis, Elsevier, vol. 8(1), pages 53-65.
    14. Davidson, James, 2002. "A model of fractional cointegration, and tests for cointegration using the bootstrap," Journal of Econometrics, Elsevier, vol. 110(2), pages 187-212, October.
    15. Barkoulas, John T. & Baum, Christopher F., 1998. "Fractional dynamics in Japanese financial time series," Pacific-Basin Finance Journal, Elsevier, vol. 6(1-2), pages 115-124, May.
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    Cited by:

    1. Assaf, A., 2006. "Dependence and mean reversion in stock prices: The case of the MENA region," Research in International Business and Finance, Elsevier, vol. 20(3), pages 286-304, September.
    2. Abdul Aziz Karia & Imbarine Bujang & Ismail Ahmad, 2013. "Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially overdifference," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(12), pages 2735-2748, December.
    3. Saâdaoui, Foued & Rabbouch, Hana, 2024. "Financial forecasting improvement with LSTM-ARFIMA hybrid models and non-Gaussian distributions," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    4. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    5. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.
    6. Xiu, Jin & Jin, Yao, 2007. "Empirical study of ARFIMA model based on fractional differencing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 138-154.
    7. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.

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