Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian

21 Pages Posted: 8 Jul 2015

See all articles by Torben G. Andersen

Torben G. Andersen

Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); Aarhus University - CREATES

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Francis X. Diebold

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Paul Labys

Charles River Associates (CRA) - Utah Office

Multiple version iconThere are 2 versions of this paper

Date Written: July 7, 2015

Abstract

It is well known that high-frequency asset returns are fat-tailed relative to the Gaussian distribution, and that the fat tails are typically reduced but not eliminated when returns are standardized by volatilities estimated from popular ARCH and stochastic volatility models. We consider two major dollar exchange rates, and we show that returns standardized instead by the realized volatilities of Andersen, Bollerslev, Diebold and Labys (2000a) are very nearly Gaussian. We perform both univariate and multivariate analyses, and we trace the differing effects of the different standardizations to differences in information sets.

Keywords: high-frequency data; integrated volatility; realized volatility; risk management

JEL Classification: C10, C22, C32, G15, G12

Suggested Citation

Andersen, Torben G. and Bollerslev, Tim and Diebold, Francis X. and Labys, Paul, Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian (July 7, 2015). Multinational Finance Journal, Vol. 4, No. 3/4, p. 159-179, 2000. Available at SSRN: https://ssrn.com/abstract=2627652

Torben G. Andersen (Contact Author)

Northwestern University - Kellogg School of Management ( email )

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Tim Bollerslev

Duke University - Finance ( email )

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Francis X. Diebold

University of Pennsylvania - Department of Economics ( email )

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National Bureau of Economic Research (NBER)

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Paul Labys

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