A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

Autor: Asger Lunde, Peter Reinhard Hansen, Ilya Archakov, Guillaume Horel
Rok vydání: 2015
Předmět:
Zdroj: SSRN Electronic Journal.
ISSN: 1556-5068
DOI: 10.2139/ssrn.3178925
Popis: 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.
Databáze: OpenAIRE