Time and Frequency Domain Analysis of Volatility Spillovers across Financial Asset Classes in Malaysia

Authors

  • Muhammad Asim Sukkur IBA University, 65200 Sukkur, Sindh, Pakistan Author
  • Waseem Sajjad Sukkur IBA University, 65200 Sukkur, Sindh, Pakistan Author
  • Suresh Kumar Sukkur IBA University, 65200 Sukkur, Sindh, Pakistan Author
  • Hyder Ali Sukkur IBA University, 65200 Sukkur, Sindh, Pakistan Author

DOI:

https://doi.org/10.61506/01.00288

Keywords:

Malaysian Financial Assets, Volatiltiy spillover, Connectedness, Time and frequency Domain

Abstract

This paper investigates the connectness and spillovers among classes of financial asset in Malaysia in the post-decade of global financial crisis. First, the Diebold & Yilmaz (2012)’s time-domain analysis is applied with the spillover index reported at 10.7%. This implies a low level of connectedness but possible diversification among different asset classes across time. Furthermore, most of the assets except foreign exchanges, are net reciever of volatility. Second, the Barunik & Krehlik (2018)’s frequency-domain analysis reveals that, at higher frequencies, the degree of connectedness increases and, the net transmitter of volatility spillovers across financial markets is contingent on the frequency under consideration. By frequency domain, the role of Gold in long run from transmitter to receiver has emerged, and there is also increase in magnitude of spillover from oil prices. The findings are insightful for risk assessment and portfolio diversification.

References

Baruník, J., & Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271-296.

Bouri, E., de Boyrie, M. E., & Pavlova, I. (2017). Volatility transmission from commodity markets to sovereign CDS spreads in emerging and frontier countries. International Review of Financial Analysis, 49, 155-165.

Central Intellegence Agency. (2017). Malaysia. The world factbook.

Cheung, W., Fung, S., & Tsai, S.-C. (2010). Global capital market interdependence and spillover effect of credit risk: evidence from the 2007–2009 global financial crisis. Applied Financial Economics, 20(1-2), 85-103.

Chong, J., & Hurn, S. (2017). Testing for speculative bubbles: Revisiting the rolling window. Queensland University of Technology. Retrieved from

Coin.dance. (2020).

Conrad, C., Custovic, A., & Ghysels, E. (2018). Long-and short-term cryptocurrency volatility components: A GARCH-MIDAS analysis. Journal of Risk and Financial Management, 11(2), 23.

Department of statistics Malaysia. (2016). Malaysia Economic Statistics - Time Series 2016.

Dewandaru, G., Masih, R., Bacha, O. I., & Masih, A. M. M. (2017). The role of Islamic asset classes in the diversified portfolios: mean variance spanning test. Emerging Markets Review, 30, 66-95.

Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66.

Dorsman, A., Koch, A., Jager, M., & Thibeault, A. (2013). Adding oil to a portfolio of stocks and bonds? Energy Economics and Financial Markets (pp. 197-213): Springer.

Ibragimov, R., Jaffee, D., & Walden, J. (2011). Diversification disasters. Journal of financial economics, 99(2), 333-348.

Ibrahim, M. H. (2012). Financial market risk and gold investment in an emerging market: the case of Malaysia. International Journal of Islamic and Middle Eastern Finance and Management, 5(1), 25-34.

Kang, S. H., McIver, R., & Yoon, S.-M. (2017). Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets. Energy Economics, 62, 19-32.

Malaysia Energy information Hub. (2020).

Mensi, W., Hammoudeh, S., Al-Jarrah, I. M. W., Sensoy, A., & Kang, S. H. (2017). Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications. Energy economics, 67, 454-475.

Mensi, W., Hammoudeh, S., & Kang, S. H. (2015). Precious metals, cereal, oil and stock market linkages and portfolio risk management: Evidence from Saudi Arabia. Economic Modelling, 51, 340-358.

National Property Information centre. (2008). The Malaysian House Price Index. Pillaiyan, S. (2015). Macroeconomic drivers of house prices in Malaysia. Canadian Social Science, 11(9), 119-130.

Raza, N., Shahzad, S. J. H., Tiwari, A. K., & Shahbaz, M. (2016). Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. Resources Policy, 49, 290-301.

Robiyanto, R. (2017). Testing commodities as safe haven and hedging instrument on asean's five stock markets. Jurnal Ekonomi Kuantitatif Terapan, 10(2).

Tiwari, A. K., Cunado, J., Gupta, R., & Wohar, M. E. (2018). Volatility spillovers across global asset classes: Evidence from time and frequency domains. The Quarterly Review of Economics and Finance, 70, 194-202.

Van Vuuren, G., & Yacumakis, R. (2015). Hedge fund performance evaluation using the Kalman filter. Studies in Economics and Econometrics, 39(3), 1-23.

Wong, H. T. (2019). Volatility spillovers between real exchange rate returns and real stock price returns in Malaysia. International Journal of Finance & Economics, 24(1), 131-149.

World Gold Council. (2019). Gold supply and demand statistics. Xu, W., Ma, F., Chen, W., & Zhang, B. (2019). Asymmetric volatility spillovers between oil and stock markets: Evidence from China and the United States. Energy Economics.

Yang, Z., & Zhou, Y. (2016). Quantitative easing and volatility spillovers across countries and asset classes. Management Science, 63(2), 333-354.

Yoon, S.-M., Al Mamun, M., Uddin, G. S., & Kang, S. H. (2018). Network connectedness and net spillover between financial and commodity markets. The North American Journal of Economics and Finance.

You-How, G., Lai-Kwan, C., Yoke-Chin, K., & Chooi-Yi, W. (2018). Information Spillover Between Crude Oil and Stock Markets: Evidence from Subsidy Cut for RON95 Fuel Price in Malaysia. Global Business Review, 19(4), 889-901.

Downloads

Published

2024-06-01

Issue

Section

Articles

How to Cite

Asim, M. ., Sajjad, W. ., Kumar, S. ., & Ali, H. (2024). Time and Frequency Domain Analysis of Volatility Spillovers across Financial Asset Classes in Malaysia. Bulletin of Business and Economics (BBE), 13(2), 14-21. https://doi.org/10.61506/01.00288

Similar Articles

1-10 of 258

You may also start an advanced similarity search for this article.