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J. Risk Financial Manag. 2017, 10(1), 7; doi:10.3390/jrfm10010007

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
Received: 10 October 2016 / Revised: 12 December 2016 / Accepted: 31 January 2017 / Published: 7 February 2017
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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. 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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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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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