Volatility and Liquidity Comparison of Indonesian and Singapore Stock Market in COVID-19 Mobility Restrictions Era

Authors

  • Irene Nathania Atma Jaya Catholic University of Indonesia
  • Sumani Atma Jaya Catholic University of Indonesia

DOI:

https://doi.org/10.21512/bbr.v14i3.9063

Keywords:

volatility, liquidity, Indonesian Stock Market, Singapore Stock Market, COVID-19 mobility restrictions era

Abstract

The COVID-19 case found at the end of December 2019 became a pandemic in March 2020. The research aimed to see and understand the differences in the performance of the Indonesian and Singapore stock indices represented by the Indeks Harga Saham Indonesia (IHSG) and Straits Times Index (STI) before and after the implementation of community mobility restrictions (Pembatasan Sosial Berskala Besar (PSBB) in Indonesia and Circuit Breaker in Singapore). The stock index data were stock index prices at closing and stock trading volume. The stock index performance was measured by its volatility and liquidity. Meanwhile, data volatility with heteroscedasticity symptoms were measured using the GARCH (1,1) model. Meanwhile, the standard deviation was used to measure homoscedastic data. The results show differences in return volatility and stock index liquidity before and after restrictions on community mobility. The return volatility of the IHSG and STI is higher before the community mobility restrictions compared to the period after. IHSG experiences liquidity after PSBB I and before PSBB II. The conclusion indicates that liquidity in Indonesia does not improve when PSBB I is implemented, but it improves in PSBB II. Meanwhile, STI’s liquidity is higher in the period after the implementation of Circuit Breaker. These results indicate that implementing the Circuit Breaker helps to improve the stock index’s performance in Singapore because volatility decreases when the policy is implemented. The policy also reduces the liquidity of the Singapore stock index.

Dimensions

Plum Analytics

Author Biographies

Irene Nathania, Atma Jaya Catholic University of Indonesia

Management Study Program, Faculty of Economic and Business

Sumani, Atma Jaya Catholic University of Indonesia

Management Study Program, Faculty of Economic and Business

References

AL-Najjar, D. M. (2016). Modelling and estimation of volatility using ARCH/GARCH models in Jordan’s Stock Market. Asian Journal of Finance & Accounting, 8(1), 152–167. https://doi.org/10.5296/ajfa.v8i1.9129

Alaoui Mdaghri, A., Raghibi, A., Thanh, C. N., & Oubdi, L. (2021). Stock market liquidity, the great lockdown and the COVID-19 global pandemic nexus in MENA countries. Review of Behavioral Finance, 13(1), 51–68. https://doi.org/10.1108/RBF-06-2020-0132

Albulescu, C. T. (2020). COVID-19 and the United States financial markets’ volatility. Finance Research Letters, 38(January), 1–5. https://doi.org/10.1016/j.frl.2020.101699

Anh, D. L. T., & Gan, C. (2021). The impact of the COVID-19 lockdown on stock market performance: Evidence from Vietnam. Journal of Economic Studies, 48(4), 836–851. https://doi.org/10.1108/JES-06-2020-0312

Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37(November), 1–10. https://doi.org/10.1016/j.frl.2020.101748

Bai, L., Wei, Y., Wei, G., Li, X., & Zhang, S. (2020). Infectious disease pandemic and permanent volatility of international stock markets: A long-term perspective. Finance Research Letters, 40(May), 1–10. https://doi.org/10.1016/j.frl.2020.101709

Baig, A. S., Butt, H. A., Haroon, O., & Rizvi, S. A. R. (2021). Deaths, panic, lockdowns and US equity markets: The case of COVID-19 pandemic. Finance Research Letters, 38(January), 1–9. https://doi.org/10.1016/j.frl.2020.101701

Bawdekar, A. A., & Prusty, B. R. (2022). Selection of stationarity tests for time series forecasting using reliability analysis. Mathematical Problems in Engineering, 2022, 1–8. https://doi.org/10.1155/2022/5687518

Burhani, F. J., Fariyanti, A., & Jahroh, S. (2013). Analisis volatilitas harga daging sapi potong dan daging ayam broiler di Indonesia. Forum Agribisnis : Agribusiness Forum, 3(2), 129–146.

Castro, M. M. S., Calisto, E. O., & Cabello-Rosales, A. (2021). US equity market volatility index components, impact on the industrial production index and post COVID-19 forecasting: Relevance to Mexico. Contaduría y Administración, 65(5), 1–26.

Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 1–17. https://doi.org/10.3390/jrfm13090208

Ekananda, M. (2018). Analisis ekonometrika untuk keuangan: Untuk penelitian bisnis dan keuangan (1st ed.). Salemba Empat.

Fadilah, R., Askandar, N. S., & Malikah, A. (2018). Penghitungan Value at Risk (VAR) portofolio optimum saham perusahaan berbasis syariah dengan pendekatan Exponentially Weighted Moving Average (EWMA) (Studi kasus pada perusahaan yang terdaftar di Jakarta Islamic Index periode Juni 2016-November 2017). E-JRA, 7, 90–103.

Haroon, O., & Rizvi, S. A. R. (2020). Flatten the curve and stock market liquidity–An inquiry into emerging economies. Emerging Markets Finance and Trade, 56(10), 2151–2161. https://doi.org/10.1080/1540496X.2020.1784716

Hartati, & Saluza, I. (2017). Aplikasi GARCH dalam mengatasi volatilitas pada data keuangan. Jurnal Matematika, 7(2), 107–118. https://doi.org/10.24843/jmat.2017.v07.i02.p87

Kanal, F. A., Manurung, T., & Prang, J. D. (2018). Penerapan model GARCH (Generalized Autoregressive Conditional Heteroscedasticity) dalam menghitung nilai beta saham Indeks Pefindo25. Jurnal Ilmiah Sains, 18(2), 67–74. https://doi.org/10.35799/jis.18.2.2018.19732

Karnadi, E. B. (2017). Panduan Eviews sederhana untuk ekonometrika dasar. Grasindo.

Laily, V. O. N., Warsito, B., & Maruddani, D. A. I. (2018). Comparison of ARCH/GARCH model and Elman recurrent neural network on data return of closing price stock. Journal of Physics: Conference Series, 1025, 1–11. https://doi.org/10.1088/1742-6596/1025/1/012103

Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020). The COVID-19 outbreak and affected countries stock markets response. International Journal of Environmental Research and Public Health, 17(8), 1–19. https://doi.org/10.3390/ijerph17082800

Ma, L., Hu, C., Lin, R., & Han, Y. (2018). ARIMA model forecast based on EViews software. In IOP Conference Series: Earth and Environmental Science (Vol. 208, No. 1). IOP Publishing. https://doi.org/10.1088/1755-1315/208/1/012017

Mashabi, S. (2020). Daftar 18 daerah yang terapkan PSBB, dari Jakarta hingga Makassar. Retrieved October 20th, 2020, from https://nasional.kompas.com/read/2020/04/20/05534481/daftar-18daerah-yang-terapkan-psbb-dari-jakarta-hingga-makassar?page=all

Ministry of Health Singapore. (2020a). Confirmed imported case of novel coronavirus infection in Singapore; Multi-ministry taskforce ramps up precautionary measures. Retrieved November 10th, 2020, from https://www.moh.gov.sg/news-highlights/details/confirmedimported-case-of-novel-coronavirus-infection-in-singapore-multi-ministrytaskforce-ramps-up-precautionary-measures%0A

Ministry of Health Singapore. (2020b). COVID-19 (temporary measures) act 2020. Retrieved from https://sso.agc.gov.sg/SL-Supp/S254-2020/Published

Nguyen, N. H., Vu, N. T., Tran, Q., Tran, T., & Vo, D. H. (2022). Market performance and volatility during the COVID-19 pandemic in Vietnam: A sector-based analysis. Cogent Business & Management, 9(1), 1–12. https://doi.org/10.1080/23311975.2022.2119681

Nurdina, Sidharta, R. Y., & Mochklas, M. (2021). Inefficient markets, anomalies, and investor behavior: A literature review. International Journal of Economics, Business and Accounting Research (IJEBAR), 5(2), 354–374.

P., H. (2020). JP Morgan: Bitcoin dicari milenial, emas pilihan orang tua. Retrieved July 7th, 2021, from https://www.cnbcindonesia.com/tech/20200807165000-37-178297/jp-morgan-bitcoin-dicari-milenial-emas-pilihan-orang-tua

Phan, D. H. B., & Narayan, P. K. (2020). Country responses and the reaction of the stock market to COVID-19—A preliminary exposition. Emerging Markets Finance and Trade, 56(10), 2138–2150. https://doi.org/10.1080/1540496X.2020.1784719

Raneo, A. P., & Muthia, F. (2018). Penerapan model GARCH dalam peramalan volatilitas di Bursa Efek Indonesia. Jurnal Manajemen dan Bisnis Sriwijaya, 16(3), 194–202. https://doi.org/10.29259/jmbs.v16i3.7462

Riyanto, S., & Hatmawan, A. A. (2020). Metode riset penelitian kuantitatif penelitian di bidang manajemen, teknik, pendidikan dan eksperimen. Depublish.

Sekaran, U., & Bougie, R. (2017). Metode penelitian untuk bisnis: Pendekatan pengembangan-keahlian (6th ed.). Salemba Empat.

Silvia, V. (2020). Statistik deskriptif. Penerbit Andi.

Sutrisno, B. (2020). The determinants of stock price volatility in Indonesia. EAJ (Economics and Accounting Journal), 3(1), 73–79. https://doi.org/10.32493/eaj.v3i1.y2020.p73-79

Thangamuthu, M., Maheshwari, S., & Naik, D. R. (2022). Volatility spillover effects during pre-and-post COVID-19 outbreak on Indian market from the USA, China, Japan, Germany, and Australia. Journal of Risk and Financial Management, 15(19), 1–15. https://doi.org/10.3390/jrfm15090378

Wulandari, H. D., Mustafid, & Yasin, H. (2018). Penerapan metode Exponentially Weighted Moving Average (EWMA) dalam pengukuran risiko inevstasi saham portofolio untuk volatilitas heterogen. Jurnal Gaussian, 7(3), 248–259. https://doi.org/10.14710/j.gauss.v7i3.26658

Yolanda, N. B., Nainggolan, N., & Komalig, H. A. H. (2017). Penerapan model ARIMA-GARCH untuk memprediksi harga saham Bank BRI. Jurnal MIPA UNSRAT Online, 6(2), 92–96. https://doi.org/10.35799/jm.6.2.2017.17817

Yousaf, I., Bouri, E., Ali, S., & Azoury, N. (2021). Gold against Asian Stock Markets during the COVID-19 outbreak. Journal of Risk and Financial Management, 14(4), 1–23. https://doi.org/10.3390/jrfm14040186

Zaremba, A., Kizys, R., Aharon, D. Y., & Demir, E. (2020). Infected markets: Novel coronavirus, government interventions, and stock return volatility around the globe. Finance Research Letters, 35(July), 1–7. https://doi.org/10.1016/j.frl.2020.101597

Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36(October), 1–6. https://doi.org/10.1016/j.frl.2020.101528

Downloads

Published

2023-10-17
Abstract 389  .
PDF downloaded 546  .