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Testing for changing volatility

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  • Jilin Wu
  • Zhijie Xiao

Abstract

In this paper, we propose a consistent U‐statistic test with good sampling properties to detect changes in volatility. We show that the test has a limiting standard normal distribution under the null hypothesis, and that it is powerful compared with various alternatives. A Monte Carlo experiment is conducted to highlight the merits of the proposed test relative to other popular tests for structural changes in volatility. An empirical example is examined to demonstrate the practical application of the proposed testing method.

Suggested Citation

  • Jilin Wu & Zhijie Xiao, 2018. "Testing for changing volatility," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 192-217, June.
    • Handle: RePEc:wly:emjrnl:v:21:y:2018:i:2:p:192-217
    DOI: 10.1111/ectj.12108
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    Cited by:

    1. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    2. Kostyrka, Andreï & Malakhov, Dmitry, 2021. "Was there ever a shift: Empirical analysis of structural-shift tests for return volatility," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 110-139.

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