Measuring and Modeling Risk Using High-Frequency Data

23 Pages Posted: 1 Nov 2008

See all articles by Wolfgang Karl Härdle

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin; Charles University; National Yang Ming Chiao Tung University; Asian Competitiveness Institute

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research

Uta Pigorsch

University of Mannheim

Date Written: August 5, 2008

Abstract

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns. In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures of systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorporation and of the DJIA index.

Keywords: Realized Volatility, Realized Betas, Volatility Modeling

JEL Classification: C13, C14, C22, C52, C53

Suggested Citation

Härdle, Wolfgang Karl and Hautsch, Nikolaus and Pigorsch, Uta, Measuring and Modeling Risk Using High-Frequency Data (August 5, 2008). Available at SSRN: https://ssrn.com/abstract=1206222 or http://dx.doi.org/10.2139/ssrn.1206222

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Asian Competitiveness Institute ( email )

Singapore

Nikolaus Hautsch (Contact Author)

University of Vienna - Department of Statistics and Operations Research ( email )

Kolingasse 14
Vienna, A-1090
Austria

Uta Pigorsch

University of Mannheim ( email )

Universitaetsbibliothek Mannheim
Zeitschriftenabteilung
Mannheim, 68131
Germany

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