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On the online estimation of local constant volatilities

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  • Fried, Roland

Abstract

Time varying volatilities in financial time series are commonly modeled by GARCH or by stochastic volatility models. Models with piecewise constant volatilities have been proposed recently as nonparametric alternatives. Following the latter approach, a procedure for online approximation of the current volatility is constructed by combining one-sided localized estimation of the variability with sequential testing for a change in it. A robust nonparametric framework is assumed since many financial time series show tails heavier than the Gaussian. A two-sample test for a change in variability is proposed, which works well even in case of skewed distributions.

Suggested Citation

  • Fried, Roland, 2012. "On the online estimation of local constant volatilities," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3080-3090.
  • Handle: RePEc:eee:csdana:v:56:y:2012:i:11:p:3080-3090
    DOI: 10.1016/j.csda.2011.02.012
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    References listed on IDEAS

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    1. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    2. Giuseppe Cavaliere & A. M. Robert Taylor, 2008. "Time‐Transformed Unit Root Tests for Models with Non‐Stationary Volatility," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 300-330, March.
    3. Fried, Roland & Gather, Ursula, 2007. "On rank tests for shift detection in time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 221-233, September.
    4. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    5. John Randal & Peter Thomson & Martin Lally, 2004. "Non-parametric estimation of historical volatility," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 427-440.
    6. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2009. "Heteroskedastic Time Series With A Unit Root," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1228-1276, October.
    7. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2007. "Testing for unit roots in time series models with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 140(2), pages 919-947, October.
    8. Zeileis, Achim & Shah, Ajay & Patnaik, Ila, 2010. "Testing, monitoring, and dating structural changes in exchange rate regimes," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1696-1706, June.
    9. Davies, Laurie & Höhenrieder, Christian & Krämer, Walter, 2012. "Recursive computation of piecewise constant volatilities," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3623-3631.
    10. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, February.
    11. Boudt, Kris & Croux, Christophe & Laurent, Sébastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 353-367, March.
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    1. Max Wornowizki & Roland Fried & Simos G. Meintanis, 2017. "Fourier methods for analyzing piecewise constant volatilities," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(3), pages 289-308, July.

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