A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

  • Peter Reinhard HansenEmail author
  • Guillaume Horel
  • Asger Lunde
  • Ilya Archakov


We introduce a multivariate estimator of financial volatility that is based on the theory of Markov chains. The Markov chain framework takes advantage of the discreteness of high-frequency returns. We study the finite sample properties of the estimation in a simulation study and apply it to high-frequency commodity prices.


Markov chain Multivariate volatility Quadratic variation Integrated variance Realized variance High frequency data 

JEL Classification

C10 C22 C80 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Peter Reinhard Hansen
    • 1
    Email author
  • Guillaume Horel
    • 2
  • Asger Lunde
    • 3
  • Ilya Archakov
    • 4
  1. 1.European University Institute and CREATESFirenzeItaly
  2. 2.Serenitas CapitalNew YorkUSA
  3. 3.University of Aarhus and CREATESAarhus VDenmark
  4. 4.European University InstituteFirenzeItaly

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