A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

Peter Hansen, Guillaume Horel (), Asger Lunde () and Ilya Archakov
Additional contact information
Guillaume Horel: Serenitas Credit L.p., Postal: one commerce plaza, 99 washington ave ste 805-a, Albany New York 12210, USA
Asger Lunde: Aarhus University and CREATES, Postal: Department of Economics and Business, Fuglesangs Allé 4, 8210 Aarhus V, Denmark

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: 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 highfrequency commodity prices.

Keywords: Markov chain; Multivariate Volatility; Quadratic Variation; Integrated Variance; Realized Variance; High Frequency Data (search for similar items in EconPapers)
JEL-codes: C10 C22 C80 (search for similar items in EconPapers)
Pages: 34
Date: 2015-03-30
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mst, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2015-19

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