Quadratic Variation by Markov Chains

Peter Hansen and Guillaume Horel
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Guillaume Horel: Merrill Lynch, New York, Postal: Merrill Lynch, New York

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

Abstract: We introduce a novel estimator of the quadratic variation that is based on the theory of Markov chains. The estimator is motivated by some general results concerning filtering contaminated semimartingales. Specifically, we show that filtering can in principle remove the effects of market microstructure noise in a general framework where little is assumed about the noise. For the practical implementation, we adopt the discrete Markov chain model that is well suited for the analysis of financial high-frequency prices. The Markov chain framework facilitates simple expressions and elegant analytical results. The proposed estimator is consistent with a Gaussian limit distribution and we study its properties in simulations and an empirical application.

Keywords: Markov chain; Filtering Contaminated Semimartingale; 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: 57
Date: 2009-03-24
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2009-13

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