Computational Economics

, Volume 46, Issue 4, pp 575–611 | Cite as

Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis

  • Zied Ftiti
  • Aviral Tiwari
  • Amél Belanès
  • Khaled Guesmi


This paper examines the co-movements dynamics between OCDE countries with the US and Europe. The core focus is to suggest advantageous techniques allowing the investigation with respect to time and frequency, namely evolutionary co-spectral analysis and wavelet analysis. Our study puts in evidence the existence of both long run and short-run co-movements. Both interdependence and contagion are well identified across markets; but with slight differences. Both investors and policymakers can derive worthwhile information from this research. Recognizing countries sensitivity to permanent and transitory shocks enables investors to select rational investment strategies. Similarly, policymakers can make safe crisis management policies.


Contagion Interdependence Stock markets index   Evolutionary co-spectral analysis Wavelet analysis 


  1. Ahamada, I., & Ben Aissa, M. S. (2004). Testing multiple structural changes in US output gap dynamics: Non-parametric approach. The Quarterly Journal of Finance, 18, 577–586.Google Scholar
  2. Ahamada, I., & Boutahar, M. (2002). Tests for covariance stationarity and white noise, with application to Euro/US Dollar exchange rate. Economics Letters, 77, 177–186.MATHMathSciNetCrossRefGoogle Scholar
  3. Artis, M. J., Bladen-Hovell, R., & Nachane, D.M. (1992). Instability of velocity of money, a new approach based on the evolutionary spectrum. CEPR Discussion Paper, \(\text{ n }^{\circ }\,735\).Google Scholar
  4. Bae, K., Karolyi, G., & Stulz, R. (2003). A new approach to measuring financial contagion. Review of Financial Studies, 16, 716–763.CrossRefGoogle Scholar
  5. Bancel, F., & Mittoo, U. R. (2011). Financial flexibility and the impact of the global financial crisis: Evidence from France. International Journal of Managerial Finance, 7(2), 179–216.CrossRefGoogle Scholar
  6. Bekaert, G., & Harvey, C. R. (1995). Time-varying world market integration. Journal of Finance, 50, 403–444.CrossRefGoogle Scholar
  7. Benhmad, F. (2012). Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach. Economic Modelling, 29, 1505–1514.CrossRefGoogle Scholar
  8. Berger, D., Pukthuanthong, K., & Yang, J. J. (2011). International diversification with frontier markets. Journal of Financial Economics, 101, 227–242.CrossRefGoogle Scholar
  9. Bessler, D. A., & Yang, J. (2003). The structure of independence in international stock markets. Journal of International Money and Finance, 22, 261–287.CrossRefGoogle Scholar
  10. Billio, M., & Caporin, M. (2010). Market linkages, variance spillovers, and correlation stability, empirical evidence of financial contagion. Computational Statistics Data Analysis, 54, 2443–2458.MATHMathSciNetCrossRefGoogle Scholar
  11. Bodart, V., & Candelon, B. (2009). Evidences of interdependence and contagion using a frequency domain framework. Emerging Market Review, 10, 140–150.CrossRefGoogle Scholar
  12. Bouchouicha, R., & Ftiti, Z. (2012). Real estate markets and the macro economy: A dynamic coherence framework. Economic Modelling, 29, 1820–1829.CrossRefGoogle Scholar
  13. Calvo, S., & Reinhart, C. (1996). Capital flows to Latin America: Is there evidence of contagion effects? In G. Calvo, M. Goldstein, & E. Hochreiter (Eds.), Private capital flows to emerging markets after the Mexican crisis (pp. 151–171). Washington, DC: Institute for International Economics.Google Scholar
  14. Chambet, A., & Gibson, R. (2008). Financial integration, economic instability and trade structure in emerging markets. Journal of International Money and Finance, 27, 654–675.CrossRefGoogle Scholar
  15. Collins, D., & Biekpe, N. (2002). Contagion: A fear for African equity markets? Journal of Economics and Business, 55, 285–297.CrossRefGoogle Scholar
  16. Corsetti, G., Pericoli, M., & Sbracia, M. (2005). Some contagion, some interdependence: More pitfalls in tests of financial contagion. Journal International Money Finance, 24, 1177–1199.CrossRefGoogle Scholar
  17. Creti, A., Ftiti, Z., & Guesmi, K. (2014). Oil price and financial markets in the main OPEC countries. Energy Studies Revue, 20, 18–35.Google Scholar
  18. Croux, C., Forni, M., & Reichlin, L. (2001). A measure of co-movement for economic variables: Theory and empirics. Review of Economics and Statistics, 83, 232–241.CrossRefGoogle Scholar
  19. Dornbusch, R., Park, Y. C., & Claessens, S. (2000). Contagion: Understanding how it spreads. World Bank Research Observer, 15, 177–197.CrossRefGoogle Scholar
  20. Eichengreen, B., Rose, A. K., & Wyplosz, C. (1996). Contagious currency crises: First tests. Scandinavian Journal of Statistics, 98, 463–484.Google Scholar
  21. Engsted, T., & Tanggaard, C. (2004). The co-movement of US and UK stock markets. European Financial Management, 10, 593–607.CrossRefGoogle Scholar
  22. Essaadi, E., & Boutahar, M. (2010). A measure of Variability in co-movement for economic variables: A time-varying coherence Function Approach. Economics Bulletin, 30, 1054–1070.Google Scholar
  23. Fan, Y., & Gençay, R. (2010). Unit root tests with wavelets. Econometric Theory, 26, 1305–1331.Google Scholar
  24. Fernandez, V. (2005). The international CAPM and a wavelet-based decomposition of value at risk. Studies in Nonlinear Dynamics and Econometrics, 9, 1–37.ADSGoogle Scholar
  25. Forbes, K., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock markets co-movements. Journal of Finance, 57, 2223–2261.CrossRefGoogle Scholar
  26. Ftiti, Z. (2010). The macroeconomic performance of the inflation targeting policy: An approach based on the evolutionary co-spectral analysis (extension for the case of a multivariate process). Economic Modelling, 27, 468–476.CrossRefGoogle Scholar
  27. Ftiti, Z., & Essaadi, E. (2008). The transition period to inflation targeting countries. The International Journal of Economic, 2, 38–46.Google Scholar
  28. Gallegati, M. (2012). A wavelet-based approach to test for financial market contagion. Computational Statistics and Data Analysis, 56, 3491–3497.MATHMathSciNetCrossRefGoogle Scholar
  29. Gallo, G. M., & Otranto, E. (2008). Volatility spillovers, interdependence and co-movements: A Markov switching approach. Computational Statistics Data Analysis, 52, 3011–3026.MATHMathSciNetCrossRefGoogle Scholar
  30. Graham, M., Kiviaho, J., & Nikkinen, J. (2012). Integration of 22 emerging stock markets: A three-dimensional analysis. Global Finance Journal, 23, 34–47.CrossRefGoogle Scholar
  31. Graham, M., & Nikkinen, J. (2011). Co-movement of the Finnish and international stock markets: A wavelet analysis. European Journal of Finance, 17, 409–425.CrossRefGoogle Scholar
  32. Grinsted, A., & Moore, J. C. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11, 561–566.CrossRefADSGoogle Scholar
  33. Hamao, Y., Masuli, R. W., & Ng, V. (1990). Correlations in price changes and volatility across international stock markets. Review of Financial Studies, 3, 281–307.CrossRefGoogle Scholar
  34. Kaminsky, G., & Reinhart, C. (2000). On crises, contagion, and confusion. Journal of International Economics, 51, 145–168.CrossRefGoogle Scholar
  35. Kim, S., & In, F. (2005). The relationship between stock returns and inflation: New evidence from wavelet analysis. Journal of Empirical Finance, 12, 435–444.CrossRefGoogle Scholar
  36. King, M., & Wadhwani, S. (1990). Transmission of volatility between stock markets. Review of Financial Studies, 3, 5–33.CrossRefGoogle Scholar
  37. Kiviaho, J., Nikkinen, J., Piljak, V., & Rothovius, T. (2012). The co-movement dynamics of European frontier stock markets. European Financial Management,. doi:10.1111/j.1468-036X.2012.00646.x.
  38. Lee, H. S. (2004). International transmission of stock market movements: A wavelet analysis. Applied Economics Letters, 11, 197–201.CrossRefADSGoogle Scholar
  39. Lee, S. B., & Kim, K. W. (1993). Does the October 1987 crash strength then the co-movements among national stock markets? Review of Financial Economics, 3, 89–102.Google Scholar
  40. Lin, W. L., Engle, R. F., & Ito, T. (1994). Do bulls and bears move across borders? International transmission of stock returns and volatility. Review of Financial Studies, 7, 507–538.CrossRefGoogle Scholar
  41. Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics, 47, 13–37.CrossRefGoogle Scholar
  42. Loh, L. (2013). Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis. Research in International Business and Finance, 29, 1–13.CrossRefADSGoogle Scholar
  43. Longin, F., & Solnik, B. (1995). Is the correlation in international equity returns constant: 1960–1990? Journal of International Money and Finance, 14, 3–26.CrossRefGoogle Scholar
  44. Madaleno, M., & Pinho, C. (2012). International stock market indices co-movements: A new look. International Journal of Finance and Economics, 17, 89–102.CrossRefGoogle Scholar
  45. Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, 7, 77–91.Google Scholar
  46. Merton, R. (1972). An analytic derivation of the efficient portfolio frontier. Journal of Financial and Quantitative Analysis, 7, 1851–1872.CrossRefGoogle Scholar
  47. Nikkinen, J., Pynnönen, S., Ranta, M., & Vähämaa, S. (2011). Cross-dynamics of exchange rate expectations: A wavelet analysis. International Journal of Finance & Economics, 16(3), 205–217.CrossRefGoogle Scholar
  48. Orlov, A. (2009). Co-spectral analysis of exchange rate co-movements during Asian financial crisis. Journal of International Financial Markets Institutions & Money, 19, 742–758.CrossRefGoogle Scholar
  49. Ozdemir, Z. A., & Cakan, E. (2007). Non-linear dynamic linkages in the international stock markets. Physica A, 377, 173–180.CrossRefADSGoogle Scholar
  50. Percival, D. B., & Walden, A. T. (2000). Wavelet methods for time series analysis. Cambridge: Cambridge University Press.MATHCrossRefGoogle Scholar
  51. Pericoli, M., & Sbracia, M. (2003). A primer on financial contagion. Journal Economic Survey, 17, 571–608.CrossRefGoogle Scholar
  52. Priestley, M. B. (1965). Evolutionary spectra for non-stationary process. Journal of the Royal Statistical Society, Series B, 27, 204–237.MATHMathSciNetGoogle Scholar
  53. Priestley, M. B. (1966). Design relations for non-stationary processes. Journal of the Royal Statistical Society, Series B, 28, 228–240.MATHMathSciNetGoogle Scholar
  54. Priestley, M. B. (1981). Spectral analysis and time series. New York: Academic Press.MATHGoogle Scholar
  55. Priestley, M. B. (1988). Non-linear and non-stationary time series analysis. London: Academic Press.Google Scholar
  56. Priestley, M. B. (1996). Wavelets and time-dependent spectral analysis. Journal of Time Series Analysis, 17(1), 85–103.MATHMathSciNetCrossRefGoogle Scholar
  57. Priestley, M. B., & Tong, H. (1973). On the analysis of bi-variate non-stationary processes. Journal of the Royal Statistical Society, Series B, 35, 135–166.Google Scholar
  58. Rua, A. (2010). Measuring co-movement in the time-frequency space. Journal of Macroeconomics, 32, 685–691.CrossRefGoogle Scholar
  59. Ranta, M. (2013). Contagion among major world markets: A wavelet approach. International Journal of Managerial Finance, 9, 133–150.CrossRefGoogle Scholar
  60. Rodriguez, J. (2007). Measuring financial contagion: A copula approach. Journal of Empirical Finance, 14, 401–423.CrossRefGoogle Scholar
  61. Ross, S. (1976). The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13, 341–360.MathSciNetCrossRefGoogle Scholar
  62. Rua, A., & Nunes, L. C. (2009). International co-movement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16, 632–639.CrossRefGoogle Scholar
  63. Sharkasi, A., Ruskin, H., & Crane, M. (2005). Interrelationships among international stock market indices: Europe, Asia and the Americas. International Journal of Theoretical and Applied Finance, 8, 1–18.MathSciNetCrossRefGoogle Scholar
  64. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19, 425–442.Google Scholar
  65. Tiwari, A. K. (2013). Decomposing time-frequency relationship between interest rates and share prices in India through wavelets. Economia Internazionale/International Economics, 66(4), 515–531.Google Scholar
  66. Tiwari, A. K., & Olayeni, O. R. (2013). Oil prices and trade balance: A wavelet based analysis for India. Economics Bulletin, 33, 2270–2286.Google Scholar
  67. Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79, 61–78.CrossRefADSGoogle Scholar
  68. Wang, M. C., & Shih, F. M. (2013). Time-varying world and regional integration in emerging European equity markets. European Financial Management, 19, 703–729.CrossRefGoogle Scholar
  69. Wu, C., & Su, Y. (1998). Dynamic relations among international stock markets. International Review of Economics and Finance, 7, 63–84.MathSciNetCrossRefGoogle Scholar
  70. Zaki, E., Bah, R., & Rao, A. (2011). Assessing probabilities of financial distress of banks in UAE. International Journal of Managerial Finance, 7(3), 304–320.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Zied Ftiti
    • 1
  • Aviral Tiwari
    • 2
  • Amél Belanès
    • 3
    • 4
  • Khaled Guesmi
    • 5
    • 6
  1. 1.EDC Paris Business SchoolOCRE-EDCCourbevoie cedex, ParisFrance
  2. 2.Faculty of Applied EconomicsICFAI University TripuraAgartalaIndia
  3. 3.High Institute of Management of Tunis, GEF-2A LaboratoryTunisTunisia
  4. 4.Department of Finance, ESSECUniversity of TunisTunisTunisia
  5. 5.IPAG Business School, IPAG-LabParisFrance
  6. 6.University Paris West La Défense, EconomiX (UMR CNRS 7235)ParisFrance

Personalised recommendations