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The estimation for Lévy processes in high frequency data

Author

Listed:
  • Jing Zheng
  • Wentao Gu
  • Baolin Xu
  • Zongwu Cai

Abstract

In this article, a generalized Lévy model is proposed and its parameters are estimated in high-frequency data settings. An infinitesimal generator of Lévy processes is used to study the asymptotic properties of the drift and volatility estimators. They are consistent asymptotically and are independent of other parameters making them better than those in Chen et al. (2010). The estimators proposed here also have fast convergence rates and are simple to implement.

Suggested Citation

  • Jing Zheng & Wentao Gu & Baolin Xu & Zongwu Cai, 2018. "The estimation for Lévy processes in high frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1051-1066, November.
  • Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1051-1066
    DOI: 10.1080/07474938.2016.1188876
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    Cited by:

    1. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).

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