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It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model

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Author Info

  • Stefano Grassi

    ()
    (Aarhus University and CREATES)

  • Paolo Santucci de Magistris

    ()
    (Aarhus University and CREATES)

Abstract

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with time varying parameters. The parameters are estimated by means of a sequential indirect inference procedure which adopts as auxiliary model a time-varying generalization of the HAR model for the realized volatility series. It emerges that during the recent financial crisis the relative weight of the daily component dominates over the monthly term. The estimates of the two factor stochastic volatility model suggest that the change in the dynamic structure of the realized volatility during the financial crisis is due to the increase in the volatility of the persistent volatility term. As a consequence of the dynamics in the stochastic volatility parameters, the shape and curvature of the volatility smile evolve trough time.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2013-03.

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Length: 42
Date of creation: 02 2013
Date of revision:
Handle: RePEc:aah:create:2013-03

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Time-Varying Parameters; On-line Kalman Filter; Simulation-based inference; Predictive Likelihood; Volatility Factors;

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References

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Cited by:
  1. Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim & Beatrice D. Simo-Kengne, 2013. "Forecasting China’s Foreign Exchange Reserves Using Dynamic Model Averaging: The Role of Macroeconomic Fundamentals, Financial Stress and Economic Uncertainty," Working Papers 201338, University of Pretoria, Department of Economics.
  2. Goodness C. Aye & Rangan Gupta & Shawkat Hammoudeh & Won Joong Kim, 2014. "Forecasting the Price of Gold Using Dynamic Model Averaging," Working Papers 201415, University of Pretoria, Department of Economics.
  3. Gupta, Rangan & Hammoudeh, Shawkat & Kim, Won Joong & Simo-Kengne, Beatrice D., 2014. "Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 170-189.

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