Wavelet multiple correlation and cross-correlation: A multiscale analysis of euro zone stock markets
AbstractStatistical studies that consider multiscale relationships among several variables use wavelet correlations and cross-correlations between pairs of variables. This procedure needs to calculate and compare a large number of wavelet statistics. The analysis can then be rather confusing and even frustrating since it may fail to indicate clearly the multiscale overall relationship that might exist among the variables. This paper presents two new statistical tools that help to determine the overall correlation for the whole multivariate set on a scale-by-scale basis. This is illustrated in the analysis of a multivariate set of daily Eurozone stock market returns during a recent period. Wavelet multiple correlation analysis reveals the existence of a nearly exact linear relationship for periods longer than the year, which can be interpreted as perfect integration of these Euro stock markets at the longest time scales. It also shows that small inconsistencies between Euro markets seem to be just short within-year discrepancies possibly due to the interaction of different agents with different trading horizons. On the other hand, multiple cross-correlation analysis shows that the French CAC40 may lead the rest of the Euro markets at those short time scales.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) in its series BILTOKI with number 2011-04.
Date of creation: Jun 2011
Date of revision:
Postal: Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain
Other versions of this item:
- Fernández-Macho, Javier, 2012. "Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1097-1104.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-07-27 (All new papers)
- NEP-ECM-2011-07-27 (Econometrics)
- NEP-EEC-2011-07-27 (European Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2007.
"On the integrated behaviour of non-stationary volatility in stock markets,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 382(1), pages 58-65.
- Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2006. "On the integrated behaviour of non-stationary volatility in stock markets," Papers cond-mat/0607478, arXiv.org.
- Gikas A. Hardouvelis & Dimitrios Malliaropulos & Richard Priestley, 2006.
"EMU and European Stock Market Integration,"
The Journal of Business,
University of Chicago Press, vol. 79(1), pages 365-392, January.
- Jian Yang & Insik Min & Qi Li, 2003. "European Stock Market Integration: Does EMU Matter?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9-10), pages 1253-1276.
- Gallegati Marco & Gallegati Mauro, 2007. "Wavelet Variance Analysis of Output in G-7 Countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(3), pages 1-25, September.
- Jussi Nikkinen & Seppo Pynnönen & Mikko Ranta & Sami Vähämaa, 2011. "Cross‐dynamics of exchange rate expectations: a wavelet analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(3), pages 205-217, 07.
- Bartram, Sohnke M. & Taylor, Stephen J. & Wang, Yaw-Huei, 2007. "The Euro and European financial market dependence," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1461-1481, May.
- Aguiar-Conraria, Luís & Azevedo, Nuno & Soares, Maria Joana, 2008. "Using wavelets to decompose the time–frequency effects of monetary policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2863-2878.
- Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
- Fratzscher, Marcel, 2001.
"Financial market integration in Europe: on the effects of EMU on stock markets,"
Working Paper Series
0048, European Central Bank.
- Fratzscher, Marcel, 2002. "Financial Market Integration in Europe: On the Effects of EMU on Stock Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 7(3), pages 165-93, July.
- Fratzscher, M., 2001. "Financial Market Integration in Europe: On the Effects of EMU on Stock Markets," Papers 48, Quebec a Montreal - Recherche en gestion.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alcira Macías).
If references are entirely missing, you can add them using this form.