An ARFIMA Model for Volatility Does Not Imply Long Memory

نویسندگان

  • Richard A. Ashley
  • Douglas M. Patterson
چکیده

Jiang and and Tian (2010) have estimated an ARFIMA model for stock return volatility. We argue that this result does not imply actual 'long memory' in such time series -as any kind of instability in the population mean yields apparent fractional integration as a statistical artifact. Alternative high-pass filters for studying stock market volatility data are suggested.

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تاریخ انتشار 2011