Comovement of East and West Stock Market Indexes

Yusoff, Yuzlizawati and Masih, Mansur (2014): Comovement of East and West Stock Market Indexes.

Abstract

Determination of diversification strategies by investors depends on the nature and magnitude of the relationships existing between different stock markets. Therefore, it is important for international investors to understand the relationship among various markets in order to diversify risk and derive high return. In a co-movement analysis a consideration that is being looked upon is the distinction between the short and the long term investor, who have different term objectives. Wavelets were used to assess the comovement and interactions of East and West stock index, namely; FBKLCI (Malaysia), FSSTI (Singapore), INDU (Indonesia), HIS (Hong Kong) and JCI (New York). The findings suggest that most of the indexes investigated in this study through the wavelet coherency shows that high coherency exists among them on the daily time scale of 32 to 512 days band. A negative correlation between them was also found among the markets, which shows a tendency in the correlation coefficients to move downwards with the timescale, except for the very long-run. In addition, it is also observed that there exists a linear relationship between the wavelet variance and wavelet timescale. The variance for most of the indexes decreases as the wavelet timescale increases. The cross correlation analysis showed that the short and medium term fluctuations for the indexes are more closely related compared to those over the long term.

• Item Type: MPRA Paper
• Language: English
• Keywords: comovement of international stocks, wavelet analysis (CWT and MODWT)
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

References

Aguiar-Conraria, L. and M.J. Soares (2011). Oil and the macroeconomy : using wavelets to analyze old issue, NIPE Working paper 16.

Candelion, B., Piplack, J. and Straetmans, S. (2008). On measuring synchronization of bulls and bears: The case of East Asia, Journal of Banking and Finance, 9(1), 23-45

Gallegati, M. and Gallagati, M. (2007). Wavelet variance analysis of output in g-7 countries, Studies in non-linear Dynamics and Econometrics, 11 (3), 1-25

Gujarati, D.N. and Porter, Dawn, C. (2009). Basic Econometrics, McGraw Hill, 5th Edition, New York

In, F. and Kim, S. (2013). An introduction to wavelet theory in finance: a wavelet multiscale approach, World Scientific Publishing.

Karolyi, G.A. and Stuls, R.M. (1996). Why do markets move together? An investigation of US-Japan stock market movements, Journal of Finance, 51(3), 951-986

Kim, S. and In, F.H. (2003). The relationship between financial variables and real economic activity : evidence from spectral and wavelet analysis, Studies in Nonlinear Dynamics and Econometrics, 7(4), 22-45

Kizys, R. and Pierdzioch, C. (2009). Changes in the international comovement of stock returns and asymmetric macroeconomic shocks, Journal of International Financial Markets, 19(2), 289-305

Lee, S.H. (2004). International transmission of stock market movements: a wavelet analysis, Applied Economics Letters, 11(3), 197-201

Madaleno, M. & Pinho, C. (2010). Relationship of the multiscale variability on the world indices, Revista de economia financier, 20, 69-92

Percival, D.B. and Walden, A.T. (2000). Wavelet methods for time series analysis. Cambridge University Press.

Pesaran, B, and Pesaran, M.H. (2009). Time Series Econometrics Using Microfit 5.0, Oxford

Ramsey, J.B. and Lampart, C. (1998). The decomposition, of economic relationship by time scale using wavelets: money and income, Macroeconomics dynamics, 2, 49-71

Rua, A. and Nunes, L.C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 1-22

Vacha, L. and Barunik. J. (2012). Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis, Energy Economics, 34, 241-247