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On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts

Christopher Krauss () and Klaus Herrmann ()
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Christopher Krauss: University of Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany
Klaus Herrmann: University of Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany

Journal of Risk and Financial Management, 2017, vol. 10, issue 1, 1-24

Abstract: This paper establishes a selection of stylized facts for high-frequency cointegrated processes, based on one-minute-binned transaction data. A methodology is introduced to simulate cointegrated stock pairs, following none, some or all of these stylized facts. AR(1)-GARCH(1,1) and MR(3)-STAR(1)-GARCH(1,1) processes contaminated with reversible and non-reversible jumps are used to model the cointegration relationship. In a Monte Carlo simulation, the power and size properties of ten cointegration tests are assessed. We find that in high-frequency settings typical for stock price data, power is still acceptable, with the exception of strong or very frequent non-reversible jumps. Phillips–Perron and PGFF tests perform best.

Keywords: cointegration testing; high-frequency; stylized facts; conditional heteroskedasticity; smooth transition autoregressive models (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2017
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