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Random walks with drift : a sequential approach

  • Steland, Ansgar
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    In this paper sequential monitoring schemes to detect nonparametric drifts are studied for the random walk case. The procedure is based on a kernel smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson estimator and its associated sequential partial sum process under non-standard sampling. The asymptotic behavior differs substantially from the stationary situation, if there is a unit root (random walk component). To obtain meaningful asymptotic results we consider local nonparametric alternatives for the drift component. It turns out that the rate of convergence at which the drift vanishes determines whether the asymptotic properties of the monitoring procedure are determined by a deterministic or random function. Further, we provide a theoretical result about the optimal kernel for a given alternative.

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    File URL: http://econstor.eu/bitstream/10419/22563/1/tr50-04.pdf
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    Paper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 2004,50.

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    Date of creation: 2004
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    Handle: RePEc:zbw:sfb475:200450
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    1. Ghysels, E. & Guay, A. & Hall, A., 1995. "Predictive Tests for Structural Change with Unknown Breakpoint," Cahiers de recherche 9524, Universite de Montreal, Departement de sciences economiques.
    2. Ferger, D., 1994. "Nonparametric detection of changepoints for sequentially observed data," Stochastic Processes and their Applications, Elsevier, vol. 51(2), pages 359-372, July.
    3. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-73, April.
    4. Ferger Dietmar, 1996. "On The Asymptotic Behavior Of Change-Point Estimators In Case Of No Change With Applications To Testing," Statistics & Risk Modeling, De Gruyter, vol. 14(2), pages 137-144, February.
    5. Davidson, James, 2002. "Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes," Journal of Econometrics, Elsevier, vol. 106(2), pages 243-269, February.
    6. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
    7. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    8. Davidson, James, 2002. "Corrigendum to "Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes": [Journal of Econometrics 106 (2) (2002) 243-269]," Journal of Econometrics, Elsevier, vol. 110(1), pages 103-104, September.
    9. Steland Ansgar, 2002. "A Bayesian View on Detecting Drifts by Nonparametric Methods," Economic Quality Control, De Gruyter, vol. 17(2), pages 177-186, January.
    10. Breitung, Jorg, 2002. "Nonparametric tests for unit roots and cointegration," Journal of Econometrics, Elsevier, vol. 108(2), pages 343-363, June.
    11. Bierens, Herman J., 1997. "Testing the unit root with drift hypothesis against nonlinear trend stationarity, with an application to the US price level and interest rate," Journal of Econometrics, Elsevier, vol. 81(1), pages 29-64, November.
    12. Jegadeesh, Narasimhan, 1991. " Seasonality in Stock Price Mean Reversion: Evidence from the U.S. and the U.K," Journal of Finance, American Finance Association, vol. 46(4), pages 1427-44, September.
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