A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

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

MoreLess

Year of publication:	2018
Authors:	Hansen, Peter Reinhard
Other Persons:	Horel, Guillaume (contributor) ; Lunde, Asger (contributor) ; Archakov, Ilya (contributor)
Publisher:	[2018]: [S.l.] : SSRN
Subject:	Theorie \| Theory \| Volatilität \| Volatility \| Markov-Kette \| Markov chain \| Multivariate Analyse \| Multivariate analysis \| ARCH-Modell \| ARCH model

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Extent:	1 Online-Ressource (34 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 7, 2015 erstellt
Other identifiers:	10.2139/ssrn.3178925 [DOI]
Classification:	C10 - Econometric and Statistical Methods: General. General ; C22 - Time-Series Models ; C80 - Data Collection and Data Estimation Methodology; Computer Programs. General
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012919202