Modeling of Jakarta Islamic Index Stock Volatility Return Pattern with Garch Model
Keywords:
GARCH, Volatility, Jakarta Islamic Index, Return, Stock
Abstract
Along with the large number of investors transacting on Islamic stocks, the movement of stock prices becomes more volatile. The purpose of this research is to examine the behavior of volatility patterns in shares incorporated in the Jakarta Islamic Index using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. This study uses daily data from six stocks contained in the Jakarta Islamic Index during the period January 1, 2009, to December 31, 2019. Data volatility is seen using the GARCH model. Estimation results for daily data show that the volatility of ASII, SMGR, TLKM, UNTR, and UNVR shares is influenced by the error and return volatility of the previous day. This is indicated by the GARCH effect on each regression result. The results of the study are beneficial for an investor, and if you want to invest with a low level of risk, you can choose TLKM shares. But if you're going to get a high level of return, you can invest in UNTR shares. For securities analysis, you can use the GARCH model that has been tested to predict volatility in the Jakarta Islamic Index.
References
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Nayak, A., Pai, M., & Pai, R. (2016). Prediction Models for Indian Stock Market. Procedia Computer Science, 89, 441–449. https://doi.org/10.1016/j.procs.2016.06.096
Oberholzer, N., & Venter, P. (2015). Univariate GARCH Models Applied to the JSE/FTSE Stock Indices. Procedia Economics and Finance, 24, 491–500. https://doi.org/10.1016/s2212-5671(15)00616-4
Rizvi, S. A., & Arshad, S. (2017). Understanding Time-varying Systematic Risks in Islamic and Conventional Sectoral Indices. Economic Modelling, 70, 1–10. https://doi.org/10.1016/j.econmod.2017.10.011
Robiyanto, R., Santoso, M. A., & Ernayani, R. (2019). Sharia Mutual Funds Performance in Indonesia. Business: Theory and Practice, 20, 11–18. https://doi.org/10.3846/btp.2019.02
Saiti, B., Bacha, O., & Masih, M. (2014). The Diversification Benefits from Islamic Investment During the Financial Turmoil: The Case for the US-based Equity Investors. Borsa Istanbul Review, 14(4), 196–211. https://doi.org/10.1016/j.bir.2014.08.002
Salisu, A., & Gupta, R. (2019). Dynamic Effects of Monetary Policy Shocks on Macroeconomic Volatility. Journal of Monetary Economics. https://doi.org/10.1016/j.jmoneco.2019.03.011
Southall, T. (2008). European Financial Markets: The Effects of European Union Membership on Central and Eastern European Equity Markets. New York: Springer Science & Business Media.
Sugiharti, L., Esquivias, M. A., & Setyorani, B. (2020). The Impact of Exchange rate Volatility on Indonesia’s Top Exports to the Five Main Export Markets. Heliyon, 6(1), e03141. https://doi.org/10.1016/j.heliyon.2019.e03141
Tan, S. D., & Tas, O. (2019). Investor Attention and Stock Returns: Evidence from Borsa Istanbul. Borsa Istanbul Review, 19(2), 106–116. https://doi.org/10.1016/j.bir.2018.10.003
Tan, Z., Yan, Z., & Zhu, G. (2019). Stock Selection with Random Forest: An Exploitation of Excess Return in the Chinese Stock Market. Heliyon, 5(8), e02310. https://doi.org/10.1016/j.heliyon.2019.e02310
Vipul, P. S. (2016). Forecasting Stock Market Volatility Using Realized GARCH Model: International evidence. Quarterly Review of Economics and Finance, 59, 222–230. https://doi.org/10.1016/j.qref.2015.07.005
Wahyudi, I., & Sani, G. A. (2014). Interdependence Between Islamic Capital Market and Money Market: Evidence from Indonesia. Borsa Istanbul Review, 14(1), 32–47. https://doi.org/10.1016/j.bir.2013.11.001
Yildiz, Y., Karan, M. B., & Pirgaip, B. (2017). Market Reaction to Grouping Equities in Stock Markets: An Empirical Analysis on Borsa Istanbul. Borsa Istanbul Review, 17(4), 216–227. https://doi.org/10.1016/j.bir.2017.08.001
Babu, N., & Reddy, E. (2015). Prediction of Selected Indian Stock Using a Partitioning–Interpolation Based ARIMA–GARCH Model. Applied Computing and Informatics, 11(2), 130–143. https://doi.org/10.1016/j.aci.2014.09.002
Birău, R., & Trivedi, J. (2015). Estimating Long-term Volatility on National Stock Exchange of India. Procedia Economics and Finance, 32(15), 574–579. https://doi.org/10.1016/s2212-5671(15)01434-3
Boako, G., Agyemang-Badu, A., & Frimpong, J. M. (2015). Volatility Dynamics In Equity Returns : A Multi-GARCH Approach. European Journal of Business and Innovation Research2, 3(4), 36–45. https://doi.org/10.1017/CBO9781107415324.004
Bodie, Z., Kane, A., & Marcus, A. (2008). Essential Of Investments 7th Edition. New York: The McGraw-Hill.
Boukhatem, J., & Moussa, F. Ben. (2018). The Effect of Islamic Banks on GDP Growth: Some Evidence from Selected MENA Countries. Borsa Istanbul Review, 18(3), 231–247. https://doi.org/10.1016/j.bir.2017.11.004
Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis Forecasting and Control. New Jersey: John Wiley & Sons, Inc.
Byström, H. (2014). The Impact of Currency Movements on Asset Value Correlations. Journal of International Financial Markets, Institutions and Money, 31(1), 178–186. https://doi.org/10.1016/j.intfin.2014.03.014
Chandrinos, S., & Lagaros, N. (2018). Construction of Currency Portfolios by Means of an Optimized Investment Strategy. Operations Research Perspectives, 5, 32–44. https://doi.org/10.1016/j.orp.2018.01.001
Enders, W. (2004). Applied Econometrics Time Series. New York: John Wiley & Sons Inc.
Engle, R. F. (1982). Autoregressive Conditional Heteroscedacity with Estimates of variance of United Kingdom Inflation. Journal of Econometrica. https://doi.org/10.2307/1912773
Erdogan, S., Gedikli, A., & Çevik, E. İ. (2020). Volatility Spillover Effects Between Islamic Stock Markets And Exchange Rates: Evidence From Three Emerging Countries. Borsa Istanbul Review, 1–21. https://doi.org/10.1016/j.bir.2020.04.003
Gold, N., Wang, Q., Cao, M., & Huang, H. (2017). Liquidity and Volatility Commonality in the Canadian Stock Market. Mathematics-in-Industry Case Studies, 8(1), 1–20. https://doi.org/10.1186/s40929-017-0016-9
Hkiri, B., Hammoudeh, S., Aloui, C., & Yarovaya, L. (2017). Are Islamic Indexes a Safe Haven for Investors? An Analysis of Total, Directional and Net Volatility Spillovers between Conventional and Islamic Indexes and Importance of Crisis Periods. Pacific Basin Finance Journal, 43, 124–150. https://doi.org/10.1016/j.pacfin.2017.03.001
Hong, Y., & Lee, Y.-J. (2017). A General Approach to Testing Volatility Models in Time Series. Journal of Management Science and Engineering, 2(1), 1–33. https://doi.org/10.3724/sp.j.1383.201001
Huber, J., Palan, S., & Zeisberger, S. (2019). Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence. Journal of Banking and Finance, 108, 1–17. https://doi.org/10.1016/j.jbankfin.2019.105635
Ismail, M. T., Audu, B., & Tumala, M. M. (2016). Volatility Forecasting with the Wavelet Transformation Algorithm GARCH Model : Evidence from African Stock Markets. The Journal of Finance and Data Science, 1–11. https://doi.org/10.1016/j.jfds.2016.09.002
Jebran, K., Chen, S., & Zubair, M. (2017). Islamic and Conventional Equity Index Co-movement and Volatility Transmission : Evidence from Pakistan. Future Business Journal, 3(2), 98–106. https://doi.org/10.1016/j.fbj.2017.05.001
Lin, Z. (2018). Modelling and Forecasting the Stock Market Volatility of SSE Composite Index using GARCH Models. Future Generation Computer Systems, 79(3), 960–972. https://doi.org/10.1016/j.future.2017.08.033
Livingston, M., Yao, P., & Zhou, L. (2019). The Volatility of Mutual Fund Performance. Journal of Economics and Business, 104, 1–19. https://doi.org/10.1016/j.jeconbus.2019.02.001
Mahapatra, S., & Bhaduri, S. (2019). Dynamics of the Impact of Currency Fluctuations on Stock Markets in India: Assessing the Pricing of Exchange Rate Risks. Borsa Istanbul Review, 19(1), 15–23. https://doi.org/10.1016/j.bir.2018.04.004
Nasr, A. Ben, Lux, T., Ajmi, A. N., & Gupta, R. (2016). Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. Regime Switching. International Review of Economics and Finance, 45, 559–571. https://doi.org/10.1016/j.iref.2016.07.014
Natarajan, V. K., Singh, A. R. R., & Priya, N. C. (2014). Examining Mean-volatility Spillovers Across National Stock Markets. Journal of Economics, Finance and Administrative Science, 19(36), 55–62. https://doi.org/10.1016/j.jefas.2014.01.001
Nayak, A., Pai, M., & Pai, R. (2016). Prediction Models for Indian Stock Market. Procedia Computer Science, 89, 441–449. https://doi.org/10.1016/j.procs.2016.06.096
Oberholzer, N., & Venter, P. (2015). Univariate GARCH Models Applied to the JSE/FTSE Stock Indices. Procedia Economics and Finance, 24, 491–500. https://doi.org/10.1016/s2212-5671(15)00616-4
Rizvi, S. A., & Arshad, S. (2017). Understanding Time-varying Systematic Risks in Islamic and Conventional Sectoral Indices. Economic Modelling, 70, 1–10. https://doi.org/10.1016/j.econmod.2017.10.011
Robiyanto, R., Santoso, M. A., & Ernayani, R. (2019). Sharia Mutual Funds Performance in Indonesia. Business: Theory and Practice, 20, 11–18. https://doi.org/10.3846/btp.2019.02
Saiti, B., Bacha, O., & Masih, M. (2014). The Diversification Benefits from Islamic Investment During the Financial Turmoil: The Case for the US-based Equity Investors. Borsa Istanbul Review, 14(4), 196–211. https://doi.org/10.1016/j.bir.2014.08.002
Salisu, A., & Gupta, R. (2019). Dynamic Effects of Monetary Policy Shocks on Macroeconomic Volatility. Journal of Monetary Economics. https://doi.org/10.1016/j.jmoneco.2019.03.011
Southall, T. (2008). European Financial Markets: The Effects of European Union Membership on Central and Eastern European Equity Markets. New York: Springer Science & Business Media.
Sugiharti, L., Esquivias, M. A., & Setyorani, B. (2020). The Impact of Exchange rate Volatility on Indonesia’s Top Exports to the Five Main Export Markets. Heliyon, 6(1), e03141. https://doi.org/10.1016/j.heliyon.2019.e03141
Tan, S. D., & Tas, O. (2019). Investor Attention and Stock Returns: Evidence from Borsa Istanbul. Borsa Istanbul Review, 19(2), 106–116. https://doi.org/10.1016/j.bir.2018.10.003
Tan, Z., Yan, Z., & Zhu, G. (2019). Stock Selection with Random Forest: An Exploitation of Excess Return in the Chinese Stock Market. Heliyon, 5(8), e02310. https://doi.org/10.1016/j.heliyon.2019.e02310
Vipul, P. S. (2016). Forecasting Stock Market Volatility Using Realized GARCH Model: International evidence. Quarterly Review of Economics and Finance, 59, 222–230. https://doi.org/10.1016/j.qref.2015.07.005
Wahyudi, I., & Sani, G. A. (2014). Interdependence Between Islamic Capital Market and Money Market: Evidence from Indonesia. Borsa Istanbul Review, 14(1), 32–47. https://doi.org/10.1016/j.bir.2013.11.001
Yildiz, Y., Karan, M. B., & Pirgaip, B. (2017). Market Reaction to Grouping Equities in Stock Markets: An Empirical Analysis on Borsa Istanbul. Borsa Istanbul Review, 17(4), 216–227. https://doi.org/10.1016/j.bir.2017.08.001
Published
2020-12-31
Section
Articles
