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Realized Laplace transforms for estimation of jump diffusive volatility models

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  • Todorov, Viktor
  • Tauchen, George
  • Grynkiv, Iaryna

Abstract

We develop an efficient and analytically tractable method for estimation of parametric volatility models that is robust to price-level jumps. The method entails first integrating intra-day data into the Realized Laplace Transform of volatility, which is a model-free estimate of the daily integrated empirical Laplace transform of the unobservable volatility. The estimation is then done by matching moments of the integrated joint Laplace transform with those implied by the parametric volatility model. In the empirical application, the best fitting volatility model is a non-diffusive two-factor model where low activity jumps drive its persistent component and more active jumps drive the transient one.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 164 (2011)
Issue (Month): 2 (October)
Pages: 367-381

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Handle: RePEc:eee:econom:v:164:y:2011:i:2:p:367-381

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: Jumps High-frequency data Laplace transform Stochastic volatility models;

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Cited by:
  1. Viktor Todorov & George Tauchen & Iaryna Grynkiv, 2011. "Volatility Activity: Specification and Estimation," Working Papers 11-23, Duke University, Department of Economics.

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