Co-movement among industry indices of Tehran Stock Exchange, Wavelet Coherence approach

Document Type : Research Paper


1 Faculty of Social sciences & Economic, Alzahra University, Tehran, Iran

2 Faculty of Economic & Administration, Urmia University, Urmia, Iran

3 Department of Science, Urmia University of Technlogy,Urmia, Iran


Co-movement analysis has a significant role in recourse allocation, risk management, etc. This study uses the novel approach of wavelet coherence in continuous wavelet transform framework to investigate the correlation dynamic and spillover effect of 10 main sector indices of Tehran Stock Exchange, in time and frequency domains. Analyzing the data indicates that correlation structure among TSE sectors is dynamic and varies over time. Besides, co-movements of industry indices have a multi-scale character. In other words, investors with different investment horizons would benefit differently if they diversify their portfolios via the same industries. In addition, results indicate that the spillover effect pattern is a scaled based phenomenon. This study suggests time scales of 2-32 days as the best time horizon for portfolio diversification.


Main Subjects

Article Title [فارسی]

بررسی هم‌حرکتی بازده در میان صنایع بورس اوراق بهادار تهران، رویکرد همبستگی موجکی

Authors [فارسی]

  • سمیه محمدی 1
  • ابراهیم عباسی 1
  • غلامرضا منصورفر 2
  • فهیمه بیگلری 3
1 گروه مدیریت، دانشکده عاوم اجتماعی و اقتصادی، دانشگاه الزهرا، تهران، ایران
2 گروه حسابداری، دانشکده اقتصاد و مدیریت، دانشگاه ارومیه، ارومیه، ایران
3 گروه ریاضی کاربردی، دانشکده علوم پایه، دانشگاه صنعتی ارومیه، ارومیه، ایران
Abstract [فارسی]

بررسی هم‌حرکتی بخش‌ها نقشی اساسی در تخصیص بهینة منابع و مدیریت ریسک دارد. این پژوهش با استفاده از رویکرد نوین همبستگی موجکی در چارچوب تبدیل موجک پیوسته، تغییر و پویایی هم‌ حرکتی بازده و اثر سرایت نوسانات شاخص ده صنعت بزرگ بورس اوراق بهادار تهران را به طور هم‌زمان در دو دامنة زمان و فرکانس بررسی می‌کند. تجزیه‌وتحلیل داده‌ها نشان‌دهندة وجود ویژگی پویایی در ساختار همبستگی میان بازده شاخص صنایع بورس اوراق بهادار تهران طی زمان است. به‌علاوه، همبستگی متقابل بازده صنایع دارای ویژگی چند مقیاسی است. به‌عبارتی دیگر سرمایه‌گذاران با افق‌های سرمایه‌گذاری مختلف، با تشکیل سبد سهام از میان صنایع یکسان به یک میزان منتفع نمی‌شوند. همچنین، الگوی سرایت نوسانات میان شاخص صنایع پدیده‌ای وابسته به مقیاس است. این پژوهش افق‌های سرمایه‌گذاری 2-32 روزه را بهترین مقیاس‌های زمانی در تنوع‌سازی پرتفوی معرفی می‌کند.

Keywords [فارسی]

  • بازده صنایع
  • تبدیل موجک پیوسته
  • سرایت‌پذیری نوسانات
  • همبستگی موجکی
  • هم‌حرکتی
Addison, P. S. (2002). The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance. CRC Press.
 Ali, S., Butt, B. Z., & Rehman, K. (2011). Comovement Between Emerging and Developed Stock Markets: An Investigation Through Cointegration Analysis. World Applied Sciences Journal, 12(4), 395-403.
Allen, D. E., & MacDonald, G. (1995). The long-run gains from international equity diversification: Australian evidence from cointegration tests. Applied Financial Economics, 5(1), 33-42.
Anderson, N., & Noss, J. (2013). The Fractal Market Hypothesis and its implications for the stability of financial markets. Bank of England Financial Stability Paper No. 23.
Barunik, J., Vacha, L., Krištoufek, L. (2011). Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data. IES Working Paper 22/2011. IES FSV. Charles University.
Behradmehr, N. (2008). Portfolio Allocation Using Wavelet Transform. (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3296955)
Bordoloi, S. D. (2009). Interdependence of US industry Sectors Using Vector AutoRegression. Master's thesis Retrieved from
Chen, M. P., Chen, P. F., & Lee, C. C. (2014). Frontier stock market integration and the global financial crisis. The North American journl of economics and finance, 29, 84-103.
Dajcman, S., Festic, M., & Kavkler, A. (2012). Comovement Dynamics between Central and Eastern European and Developed European Stock Markets during European Integration and Amid Financial Crises – A Wavelet Analysis. Inzinerine Ekonomika-Engineering Economics, 23(1), 22-32.
Farzinvash, A., Farmanara, O., & Mohammadi, S. (2013). Estimation of Optimal Hedge Ratio in Different Time-Scales: Wavelet Analysis Approach. Journal of Economic Strategy, 2(6), 7-40 (In Persian).
Gallali, M. I., & Abidi, R. (2012). A Dynamic Analysis of Financial Contagion:The Case of the Subprime Crisis. Journal of Business Studies Quarterly, 4(2), 11-27
Gallegati, M. (2008). Wavelet analysis of stock returns and aggregate economic activity. Computational Statistics & Data Analysis, 52, 3061 – 3074.
Gencay, R., Selcuk, F., & Whitcher, B. (2002). An Introduction to Wavelet and Other Filtering Methods in Finance and Economics. San Diego: Academic Press.
Grinsted, A., Moore, J., & Jevrejeva, S. (2004): Application of the cross wavelet transform and wavelet coherence to geophysical time series. Non-linear Processes in Geophysics, 11, 561-566.
Guerrieri, P., & Meliciani, V. (2005). Technology and international competitiveness: The interdependence between manufacturing and producer services. Structural Change and Economic Dynamics, 16, 489-502.
Lahrech, A., & Sylwester, K. (2011). U.S. and Latin American stock market linkages. Journal of International Money and Finance, 30, 1341-1347.
Lean, H. H., & Teng, K. T. (2013). Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach. Economic Modelling, 32, 333-342
Madaleno, M., & Pinho, C. (2010). Relationship of the Multiscale Variability on World Indices. REVISTA DE ECONOM´IA FINANCIERA,  20, 69-92.
Mansourfar, G. (2013). Econometrics and Metaheuristic Optimization Approaches to International Portfolio Diversification. Iranian Journal of Management Studies, 6(1), 45-75.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77-91.
Narayan, S., Sirananthakumar, S., Islam,S.Z. (2014). Stock market integration of emerging Asian economies: Patterns and couses. Economic Modelling, 39, 19-31
Onay, C., & Ünal, G. (2012). Cointegration and Extreme Value Analyses of Bovespa and the Istanbul Stock Exchange. Finance a úvěr (Czech Journal of Economics and Finance), 62(1), 66-91.
Ranta, M. (2010). Wavelet Multiresolution Analysis of Financial Time Series. Acta Wasaensia Paper. No. 223. ISBN 978–952–476–303–5.
Rua, A., & Nunes, L. C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16, 632-639.
Rua, A., & Nunes, L.C. (2012). A wavelet-based assessment of market  risk: The emerging markets case. Quarterly Review of Economics and Finance, 52, 84-92.
Saiti, B., Dewandaru, G., & Masih, M. (2013). A Wavelet-based Approach to Testing Shari’ah-compliant Stock Market Contagion: Evidence from the ASEAN Countries. Australian Journal of Basic and Applied Sciences, 7(7), 268-280.
Sharkasi, A., Ruskin, H. J., &  Crane, M. (2005). Interrelationships among International Stock Market Indices: Europe, Asia and the Americas. International journal of theoretical and applied finance, 8(5), 1-18.
Sifuzzaman, M., Islam, M. R., & Ali, M. Z. (2009). Application of Wavelet Transform and its Advantages Compared to Fourier Transform. Journal of Physical Sciences, 13, 121-134.
Sims, C.A.(1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48
Teulon, F., Guesmi, K., Mankai, S. (2014). Regional stock market integration in Singapore: A mulitivariate analysis. Economic modelling, 43, 217-224.
Torrence, C., & Webster, P. J. (1999). Interdecadal Changes in the ENSO–Monsoon System. Journal of Climate, 12, 2679-2690.
Vavrina, M. (2012). Comovement of Stock Markets and Commodities: A Wavelet Analysis. ( Master's thesis, Charles University, Faculty of Social Sciences, Institute of Economic Studies, Prague) . Retrieved from
Xiao, L., & Dhesi, G. (2010). Volatility spillover and time-varying conditional correlation between the European and US stock markets. Global Economy and Finance Journal, 3(2), 148-164.
You, L., & Daigler, R. T. (2010). Is international diversification really beneficial? Journal of Banking & Finance, 34, 163-173.