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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce


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Volume 24 (2020)

Temporal aggregation of random walk processes and implications for economic analysis

Yamin S Ahmad
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  • University of Wisconsin – Whitewater, Department of Economics, 800 W Main Street, Whitewater, WI 53190, USA, Phone: +(262) 472 5576, Fax: +(262) 472 4683
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/ Ivan Paya
Published Online: 2019-09-18 | DOI: https://doi.org/10.1515/snde-2017-0102

Abstract

This paper examines the impact of time averaging and interval sampling data assuming that the data generating process for a given series follows a random walk with iid errors. We provide exact expressions for the corresponding variances, and covariances, for both levels and higher order differences of the aggregated series, as well as that for the variance ratio, demonstrating exactly how the degree of temporal aggregation impacts these properties. We empirically investigate this issue on exchange rates and find that the values of the variance ratios and autocorrelation coefficients at different frequencies are consistent with our theoretical results. We also conduct a simulation exercise that illustrates the potential effect that conditional heteroskedasticity and fat tails may have on the temporal aggregation of a random walk and of a highly persistent autoregressive process.

Keywords: conditional heteroskedasticity; random walk; temporal aggregation; variance ratio

JEL Classification: C22; C19; C15; F47

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About the article

Published Online: 2019-09-18


Citation Information: Studies in Nonlinear Dynamics & Econometrics, 20170102, ISSN (Online) 1558-3708, DOI: https://doi.org/10.1515/snde-2017-0102.

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