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Volatility Clustering in High-Frequency Data: A self-fulfilling prophecy?

Author

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  • Matei Demetrescu

    () (Goethe University Frankfurt)

Abstract

Clustering volatility is shown to appear in a simple market model with noise trading simply because agents use volatility forecasting models. At the core of the argument lies a feed-back mechanism linking past observed volatility to present observed volatility. Its stability properties are critical as to what kind of volatility will ultimately be observed.

Suggested Citation

  • Matei Demetrescu, 2007. "Volatility Clustering in High-Frequency Data: A self-fulfilling prophecy?," Economics Bulletin, AccessEcon, vol. 7(15), pages 1-8.
  • Handle: RePEc:ebl:ecbull:eb-07g10014
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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

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