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Robust Testing for Fractional Integration Using the Bootstrap

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  • Andersson, Michael K.

    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Gredenhoff, Mikael P.

    (Dept. of Economic Statistics, Stockholm School of Economics)

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    Abstract

    Asymptotic tests for fractional integration are usually badly sized in small samples, even for normally distributed processes. Furthermore, tests that are well-sized under normality may be severely distorted by non-normalities and ARCH errors. This paper demonstrates how the bootstrap can be implemented to correct for such size distortions. It is shown that a well-designed bootstrap test based on the MRR and GPH tests is exact, and a procedure based on the REG test is nearly exact.

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    Bibliographic Info

    Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 218.

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    Length: 19 pages
    Date of creation: 27 Jan 1998
    Date of revision:
    Handle: RePEc:hhs:hastef:0218

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    Related research

    Keywords: Long-memory; resampling; skewness and kurtosis; ARCH; Monte Carlo; size correction.;

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    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-313, September.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, EconWPA, revised 05 Mar 1996.
    4. Horowitz, J.L., 1995. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Working Papers 95-10, University of Iowa, Department of Economics.
    5. J. L. Horowitz, 1995. "Bootstrap Methods In Econometrics: Theory And Numerical Performance," SFB 373 Discussion Papers 1995,63, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. repec:wop:humbsf:1995-63 is not listed on IDEAS
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    Cited by:
    1. Arteche, J. & Orbe, J., 2005. "Bootstrapping the log-periodogram regression," Economics Letters, Elsevier, vol. 86(1), pages 79-85, January.
    2. Christian de Peretti, 2003. "Bilateral Bootstrap Tests for Long Memory: An Application to the Silver Market," Computational Economics, Society for Computational Economics, vol. 22(2), pages 187-212, October.
    3. Arteche, Josu & Orbe, Jesus, 2009. "Using the bootstrap for finite sample confidence intervals of the log periodogram regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1940-1953, April.
    4. 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.
    5. Hatgioannides, John & Mesomeris, Spyros, 2007. "On the returns generating process and the profitability of trading rules in emerging capital markets," Journal of International Money and Finance, Elsevier, vol. 26(6), pages 948-973, October.
    6. Anthony Murphy & M Izzeldin, 2006. "Bootstrapping long memory tests: some Monte Carlo results," Working Papers 574547, Lancaster University Management School, Economics Department.
    7. Panas, E., 2001. "Long memory and chaotic models of prices on the London Metal Exchange," Resources Policy, Elsevier, vol. 27(4), pages 235-246, December.

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