The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Dynamic stock market integration driven by the European Monetary Union: An empirical analysis
Open accessAbstract
This paper investigates the impacts of the introduction of the euro on the pattern of stock market linkages and the dynamic process of stock market integration over the period from 1989-2003. On a regional level, we examine integration among stock market indices of European Union (EU) countries with the European Monetary Union (EMU) while on a global level, integration of the EMU vis-a-vis Japan and the US are analyzed. We assess stock market integration within the context of a bivariate exponential generalized autoregressive conditional heteroscedasticity (EGARCH) framework with time varying conditional correlations. First, we discuss that European stock market integration has undergone a clear regime shift. Second, we find a striking number of significant return and volatility spillovers within the EMU and for the entire EMU region with the US and Japan and that these linkages have strengthened with currency unification. Third, we show that the introduction of the euro has indeed caused this stock market integration. Finally, our seemingly unrelated regression estimations (SURE) find that stock market integration is a persistent and seasonal process as its main determinants are the existing levels of integration and stock market development and there are signs of a positive January effect. While the introduction of the monetary union has in general been a significant driving force behind this regional and global phenomenon, the effectiveness of the different economic convergence criteria associated with the EMU in driving this process differs across member states. On a global level, the commitment to price stability has significantly strengthened stock market integration between the EMU and the US whilst convergence in industrial production has increased ties between the EMU and Japan.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Newey, W. K., & West, K. D. (1987) · Econometrica · doi:10.2307/1913610 · Cited by 16,936
A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix
Newey, W., & West, K. (1986) · National Bureau of Economic Research · doi:10.3386/t0055 · Cited by 12,278
Breitung, J., & Hamilton, J. D. (1995) · Contemporary Sociology · doi:10.2307/2076916 · Cited by 10,966
Conditional Heteroskedasticity in Asset Returns: A New Approach
Nelson, D. B. (1991) · Econometrica · doi:10.2307/2938260 · Cited by 10,236
On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks
GLOSTEN, L. R., JAGANNATHAN, R., & RUNKLE, D. E. (1993) · The Journal of Finance · doi:10.1111/j.1540-6261.1993.tb05128.x · Cited by 9,008
An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
Zellner, A. (1962) · Journal of the American Statistical Association · doi:10.1080/01621459.1962.10480664 · Cited by 8,401
No Contagion, Only Interdependence: Measuring Stock Market Comovements
Forbes, K. J., & Rigobon, R. (2002) · The Journal of Finance · doi:10.1111/0022-1082.00494 · Cited by 4,615
A Theory of Optimum Currency Areas
Mundell, R. A. (1961) · Cited by 4,467
Business conditions and expected returns on stocks and bonds
Fama, E. F., & French, K. R. (1989) · Journal of Financial Economics · doi:10.1016/0304-405x(89)90095-0 · Cited by 3,933
Metadata
- Authors
- Kim, S. J., Moshirian, F., & Wu, E.
- Venue
- Journal of Banking & Finance
- Publisher
- Elsevier BV
- Published
- 2005-10
- Volume
- 29
- Issue
- 10
- Pages
- 2475-2502
- ISSN
- 0378-4266 (ISSN-L)
- OpenAlex
- W3122275744
- Cited by
- 346
- References
- 42
- FWCI
- 26.13
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dynamic stock market integration driven by the European Monetary Union: An empirical analysis. https://app.cochat.ai/papers/10.1016/j.jbankfin.2004.09.002
- The paper
- Kim, S. J., Moshirian, F., & Wu, E. (2005). Dynamic stock market integration driven by the European Monetary Union: An empirical analysis. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2004.09.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.