Abstract
This article discusses selected ways of measuring financial market integration that can be found in existing scientific literature. The main aim of this research is to characterize those integration measures which are based on principal components analysis, such as: (1) Coefficient of determination of the regression model with principal components as the regressors, (2) integration index equal to the share of variance explained by the first principal component with respect to the overall variance of the original variables, and (3) segmentation index that captures the variation in loadings of the first principal component. The above mentioned measures have been utilized to carry out a dynamic analysis of the level of integration of eurozone stock markets in the time periods: 2007–2009 and 2009–2012.
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Notes
- 1.
An extensive review of methods and tools for measuring integration can be found in Chen et al. (2014).
- 2.
This constraint ensures normalization of the components vector.
- 3.
Pukthuanthong and Roll (2009) assume 90% as an adequate value.
- 4.
A window with such length allowed to avoid the influence of short-term disturbances.
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This publication has received financial support from the Polish Ministry of Science and Higher Education under subsidy for maintaining the research potential of the Faculty of Mathematics and Informatics and Faculty of Economics and Management, University of Bialystok.
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Majewska, E., Jamroz, P. (2018). Integration Measures Based on Principal Component Analysis: Example of Eurozone Stock Markets. In: Tsounis, N., Vlachvei, A. (eds) Advances in Time Series Data Methods in Applied Economic Research. ICOAE 2018. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-02194-8_18
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