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Structural Breaks and Common Factors in the Volatility of the Fama-French Factor Portfolios

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  • Andrea Beltratti
  • Claudio Morana

Abstract

We study the time series properties of the Fama-French factor returns volatility processes. Among the original findings of this paper, we point to structural breaks in the volatility of the factors, and strong coincidence between the timing of the breaks in the volatility of the market portfolio and the timing of the breaks in the volatility of SMB. Moreover, analyses of the break free series show that two common long memory factors drive the long-run evolution of the series. The first factor mainly affects the volatility of the market and the volatility of SMB, while the second one mainly affects the volatility of HML. These results imply that the time-varing volatility of stocks is driven mainly by the time-varying volatility of the market as a whole and of the HML portfolio, while the volatility of SMB does not seem to be an independent driving force.

Suggested Citation

  • Andrea Beltratti & Claudio Morana, 2005. "Structural Breaks and Common Factors in the Volatility of the Fama-French Factor Portfolios," ICER Working Papers 23-2005, ICER - International Centre for Economic Research.
    • Handle: RePEc:icr:wpicer:23-2005
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    1. Claudio Morana, 2009. "Realized betas and the cross-section of expected returns," Applied Financial Economics, Taylor & Francis Journals, vol. 19(17), pages 1371-1381.

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    More about this item

    Keywords

    risk factors; structural change; long memory; fractional cointegration; portfolio allocation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F30 - International Economics - - International Finance - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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