Short Term Forecasting Method: Covid 19 and Capital Market in Indonesia
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Oct 26, 2022
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Abstract
This study aimed to predict the short-term confirmed Covid 19 and Jakarta Composite Index (JCI) cases in Indonesia. The prediction uses ARIMA and SutteARIMA methods, and the data processed with R software. Researcher using time series data from April 2nd, 2020 (the date of covid 19 detected in Indonesia) to September 30th, 2020. We are fitted the data with the data from October 1st to October 10th, 2020. Based on the fitted data, we could forecast the cases from October 11th to October 31st, 2020. We applied the Mean Absolute Percentage Error (MAPE) to predict accuracy measures to evaluate forecasting methods. Based on forecasting with ARIMA and SutteARIMA methods, the SutteARIMA method is more suitable than ARIMA to calculate the daily forecasts of negative Covid 19 in Indonesia with MAPE value of 0.156 (smaller than 0.21 compared to MAPE value of ARIMA). At the same time, the ARIMA method is more suitable than SutteARIMA to calculate the daily forecasts of positive Covid 19 and JCI in Indonesia. The MAPE value of 0.06 (smaller than 0.104 compared to MAPE value of SutteARIMA for positive Covid 19) and MAPE value of 0.012 (smaller than 0.021 compared to MAPE value of SutteARIMA for JCI Indonesia).
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Besti, N. (2022). Short Term Forecasting Method: Covid 19 and Capital Market in Indonesia. Jurnal Manajemen Stratejik Dan Simulasi Bisnis, 3(1), 35-48. https://doi.org/10.25077/mssb.3.1.35-48.2022
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References
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Al-awadhi, A. M., Alsaifi, K., Al-awadhi, A., & Alhammadi, S. (2020). Journal of Behavioral and Experimental Finance Death and contagious infectious diseases : Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
Ali, M., Alam, N., Aun, S., & Rizvi, R. (2020). Journal of Behavioral and Experimental Finance Coronavirus ( COVID-19 ) — An epidemic or pandemic for financial markets. Journal of Behavioral and Experimental Finance, 27, 100341. https://doi.org/10.1016/j.jbef.2020.100341
Anggraeni, R. (2020). IHSG Diprediksi Lanjutkan Pelemahan 8 Hari Beruntun.
Retrieved from https://ekbis.sindonews.com/read/1543948/178/ihsgdiprediksi-lanjutkan-pelemahan-8-hari-beruntun-1583192301
Arunkumar, K. E., Kalaga, D. V, Mohan, C., Kumar, S., & Chilkoor, G. (2021). Forecasting the dynamics of cumulative COVID-19 cases ( confirmed , recovered and deaths ) for top-16 countries using statistical machine learning models : Auto-Regressive Integrated Moving Average ( ARIMA ) and Seasonal Auto-Regressive Integrated Moving Average ( SARIMA ). Applied Soft Computing Journal, 103(December 2019), 107161. https://doi.org/10.1016/j.asoc.2021.107161
Benvenuto, D., Giovanetti, M., Vassallo, L., Angeletti, S., & Ciccozzi, M. (2020). Data in brief Application of the ARIMA model on the COVID- 2019 epidemic dataset. Data in Brief, 29, 105340. https://doi.org/10.1016/j.dib.2020.105340
Djalante, R., Lassa, J., Setiamarga, D., Sudjatma, A., Indrawan, M., Haryanto, B., … Warsilah, H. (2020). Progress in Disaster Science Review and analysis of current responses to COVID-19 in Indonesia : Period of January to March 2020 ☆. 6. https://doi.org/10.1016/j.pdisas.2020.100091
Duan, X., & Zhang, X. (2020). ARIMA modelling and forecasting of irregularly patterned COVID-19 outbreaks using Japanese and South Korean data. Data in Brief, 31, 105779. https://doi.org/10.1016/j.dib.2020.105779
Goodell, J. W. (2020). COVID-19 and finance : Agendas for future research. (March). https://doi.org/10.1016/j.frl.2020.101512
Hanck, C., Arnold, M., Gerber, A., & Schmelzer, M. (2020). Introduction to Econometrics with R.
Ilie, O., Cojocariu, R., Ciobica, A., & Timofte, S. (n.d.). Forecasting the Spreading of COVID-19 across Nine Countries from Europe , Asia , and the American Continents Using the ARIMA Models. 1–18.
Koczkodaj, W. W., Mansournia, M. A., Pedrycz, W., Wolnydominiak, A., Strza, D., Armstrong, T., … Mazurek, J. (2020). 1 , 000 , 000 cases of COVID-19 outside of China : The date predicted by a simple heuristic. (March), 0–4. https://doi.org/10.1016/j.gloepi.2020.100023
Kufel, T. (2020). ARIMA-based forecasting of the dynamics of confirmed Covid-19 cases for selected European countries ARIMA-based forecasting of the dynamics of confirmed Covid-19 cases for selected European countries Introduction Covid-19 has infected over 7 million people since its appearance , covering 114 countries ( status for 8 June 2020 ). The epidemic began in December. (October). https://doi.org/10.24136/eq.2020.009
Makridakis, Spyros. , Steven C. Wheelwright, dan Victor E. McGee. Metode dan Aplikasi Peramalan, Jakarta: Erlangga, 1999.
Mubarok, F., & Fadhli, M. M. (2020). Efficient Market Hypothesis and Forecasting of the Industrial Sector on the Indonesia Stock Exchange. 23(2), 160–168. https://doi.org/10.14414/jebav.v23i2.2240.ABSTRACT
Potensi, T., & Ekonomi, R. (2020). Tinjauan ekonomi, keuangan, & fiskal.
Rakhmawati, D., Wahyudi, R., & Yuliawan, C. G. (2019). PEMODELAN HARGA SAHAM IHSG SELAMA PANDEMI COVID-19 MENGGUNAKAN ARIMA NON MUSIMAN. 13(2), 39–48.
Roosa, K., Lee, Y., Luo, R., Kirpich, A., Rothenberg, R., Hyman, J. M., … Chowell, G. (2020). Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th , 2020. Infectious Disease Modelling, 5, 256–263. https://doi.org/10.1016/j.idm.2020.02.002
Saleh, A., & Boj, E. (2020). Science of the Total Environment SutteARIMA : Short-term forecasting method , a case : Covid-19 and stock market in Spain. Science of the Total Environment, 729, 138883. https://doi.org/10.1016/j.scitotenv.2020.138883
Science, N., Phenomena, C., Fanelli, D., & Piazza, F. (2020). Chaos , Solitons and Fractals Analysis and forecast of COVID-19 spreading in China , Italy and France. Chaos, Solitons and Fractals: The Interdisciplinary Journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena, 134, 109761. https://doi.org/10.1016/j.chaos.2020.109761
Wang, J., & Wang, X. (2020). COVID-19 and financial market efficiency : Evidence from an entropy-based analysis. Finance Research Letters, (December), 101888. https://doi.org/10.1016/j.frl.2020.101888
Wei, W.W.S., 1994. Time Series Analysis: Univariate and Multivariate Methods. Addison
Wesley Publishing Company, New York.
worldometers info. Available at https://www.worldometers.info/coronavirus/country/indonesia/ (access on 30 September 2020)
World Health Organization (WHO). Coronavirus disease (COVID-2019) situation reports-27. https://www.who.int/docs/default-source/searo/indonesia/covid19/who-situation-report-27.pdf?sfvrsn=ce8d437a_4 (Accessed 20 Sep 2020)