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

University of Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg, Germany
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Academic Editor: Teodosio Perez-Amaral
J. Risk Financial Manag. 2017, 10(1), 7; https://doi.org/10.3390/jrfm10010007
Received: 10 October 2016 / Revised: 12 December 2016 / Accepted: 31 January 2017 / Published: 7 February 2017
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. View Full-Text
Keywords: cointegration testing; high-frequency; stylized facts; conditional heteroskedasticity; smooth transition autoregressive models cointegration testing; high-frequency; stylized facts; conditional heteroskedasticity; smooth transition autoregressive models
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Krauss, C.; Herrmann, K. On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts. J. Risk Financial Manag. 2017, 10, 7.

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