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High- and Low-Frequency Exchange Rate Volatility Dynamics: Range-Based Estimation of Stochastic Volatility Models

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  • Sassan Alizadeh
  • Michael W. Brandt
  • Francis X. Diebold

Abstract

We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that the range is not only a highly efficient volatility proxy, but also that it is approximately Gaussian and robust to microstructure noise. The good properties of the range imply that range-based Gaussian quasi-maximum likelihood estimation produces simple and highly efficient estimates of stochastic volatility models and extractions of latent volatility series. We use our method to examine the dynamics of daily exchange rate volatility and discover that traditional one-factor models are inadequate for describing simultaneously the high- and low-frequency dynamics of volatility. Instead, the evidence points strongly toward two-factor models with one highly persistent factor and one quickly mean-reverting factor.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 8162.

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Date of creation: Mar 2001
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Publication status: published as Alizadeh, Sassan, Michael W. Brandt and Francis X. Diebold. "Range-Based Estimation Of Stochastic Volatility Models," Journal of Finance, 2002, v57(3,Jun), 1047-1091.
Handle: RePEc:nbr:nberwo:8162

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Cited by:
  1. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
  2. Galina Hale & Assaf Razin & Hui Tong, 2009. "The Impact of Credit Protection on Stock Prices in the Presence of Credit Crunches," NBER Working Papers 15141, National Bureau of Economic Research, Inc.
  3. Wang, Jianxin, 2007. "Foreign equity trading and emerging market volatility: Evidence from Indonesia and Thailand," Journal of Development Economics, Elsevier, vol. 84(2), pages 798-811, November.

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