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A Kolmogorov-Smirnov type test for conditional heteroskedasticity in time series

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  • Chen, Min
  • An, Hong Zhi
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    Abstract

    In this paper we propose a new test of conditional heteroskedasticity for time series by introducing a Kolmogorov-Smirnov-type test statistic. The asymptotic properties of the new test statistic are established. The results demonstrate that such a test is consistent.

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    File URL: http://www.sciencedirect.com/science/article/B6V1D-3WNMX3B-F/2/71a35a0d5b4da6421529e7c6f0184dc1
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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 33 (1997)
    Issue (Month): 3 (May)
    Pages: 321-331

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    Handle: RePEc:eee:stapro:v:33:y:1997:i:3:p:321-331

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    Related research

    Keywords: Nonlinear time series model Conditional heteroskedasticity Hypothesis testing Brownian motion;

    References

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    1. Robert F. Engle & David F. Hendry & David Trumble, 1985. "Small-Sample Properties of ARCH Estimators and Tests," Canadian Journal of Economics, Canadian Economics Association, vol. 18(1), pages 66-93, February.
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    Cited by:
    1. Xiangjin Shen & Hiroki Tsurumi, 2011. "Comparison of Bayesian Model Selection Criteria and Conditional Kolmogorov Test as Applied to Spot Asset Pricing Models," Departmental Working Papers 201126, Rutgers University, Department of Economics.
    2. Hwang, Sun Y. & Basawa, I. V., 2001. "Nonlinear time series contiguous to AR(1) processes and a related efficient test for linearity," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 381-390, May.
    3. Wolfgang Polonik & Qiwei Yao, 2008. "Testing for multivariate volatility functions using minimum volume sets and inverse regression," LSE Research Online Documents on Economics 24132, London School of Economics and Political Science, LSE Library.

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