Prediksi Harga Saham Subsektor Farmasi Menggunakan Geometric Brownian Motion
DOI:
https://doi.org/10.30865/mib.v6i1.3415Keywords:
Prediction, Stock, Farmasi, Geometric Brownian Motion, Covid-19Abstract
Investing in stocks is a popular type of investment today. During the current COVID-19 pandemic, the shares of companies in the pharmaceutical sub-sector are becoming more attractive. Stock price movements determine whether investors will increase their investment in a company or withdraw their money. To minimize the risk of investor loss, forecasting is carried out on the daily closing of stock prices. Forecasting is the best method to predict future stock prices Geometric Brownian motion is a method used to predict time series data, where random variables follow Brownian motion. In this study, simulation and analysis of stock returns and fluctuations (volatility) of 5 companies from the basic industry and chemical sector (Basic Industry & Chemicals), pharmaceutical sub-sector on the IDX will be carried out. The five companies are PT Darya-Varia Laboratoria Tbk (DVLA), PT Indofarma (Persero) Tbk (INAF), PT Kimia Farma (Persero) Tbk (KAEF), PT Kalbe Farma Tbk (KLBF), and PT Industri Jamu and Pharmaceutical Sido. Muncul Tbk (SIDO). After the Kolmogorov-Smirnov normalization test, the stocks that meet the normal distribution are KLBF and SIDO. Then the predicted MAPE value of the two stocks is calculated. The MAPE values for KLBF at 100 iterations, 1000 iterations and 10000 iterations were 2.1073%, 1.4382% and 1.2847%.. MAPE values for SIDO at 100 iterations, 1000 iterations and 10000 iterations are 2.0136%, 2.2568%, and 2.0677%.References
M. Azizah, M. I. Irawan, and E. R. M. Putri, “Comparison of stock price prediction using geometric Brownian motion and multilayer perceptron,†AIP Conf. Proc., vol. 2242, no. June, 2020, doi: 10.1063/5.0008066.
R. Sulistiawati, “Pengaruh Investasi Terhadap Pertumbuhan Ekonomi Dan Penyerapan Tenaga Kerja Serta Kesejahteraan Masyarakat Di Provinsi Di Indonesia,†J. Ekon. Bisnis dan Kewirausahaan Untan, vol. 3, no. 1, p. 10500, 2012, doi: 10.26418/jebik.v3i1.9888.
A. R. P. Barusman, Nurdiawansyah, T. L. P. Warganegara, and S. A. Mega, “Influence of company characteristics on carbon disclosure emissions on manufacturing companies in indonesia,†Int. J. Adv. Sci. Technol., vol. 29, no. 6, pp. 1423–1431, 2020.
F. I. W. Niansyah, P. Indriana, and A. Firmansyah, “Pemanfaatan Instrumen Derivatif Di Indonesia Dan Perbandingan Standar Akuntansi Terkait Derivatif,†J. Ilm. Akunt. Kesatuan, vol. 6, no. 2, pp. 140–152, 2018.
A. Ameci, A. R. P. Barusman, L. S. Amna, and R. Riswan, “Analisis Return Saham Dan Volume Perdagangan Saham Pt Bukit Asam Tbk Di Masa Pandemi Covid-19,†Visionist, vol. 10, no. 1, pp. 1–7, 2021, [Online]. Available: http://jurnal.ubl.ac.id/index.php/jmv/article/view/2027.
M. H. Nguyen, “To cite this version : Document de Travail Working Paper Forecasting and risk management in the Vietnam Stock Exchange Manh Ha Nguyen *,†2018.
A. P. Raneo and F. Muthia, “Penerapan Model GARCH Dalam Peramalan Volatilitas di Bursa Efek Indonesia,†J. Manaj. Dan Bisnis Sriwij., vol. 16, no. 3, pp. 194–202, 2019, doi: 10.29259/jmbs.v16i3.7462.
V. Maulidya, E. Apriliani, and E. R. M. Putri, “Prediksi Harga Saham Menggunakan Geometric Brownian Motion Termodifikasi Kalman Filter dengan Konstrain,†Indones. J. Appl. Math., vol. 1, no. 1, pp. 6–18, 2020.
F. U. Ulfah, “Ditopang Vaksin Corona, Bagaimana Rekomendasi Saham Farmasi?†https://market.bisnis.com/read/20201208/189/1327839/ditopang-vaksin-corona-bagaimana-rekomendasi-saham-farmasi.
S. N. Z. Abidin and M. M. Jaffar, “Forecasting share prices of small size companies in Bursa Malaysia using geometric Brownian motion,†Appl. Math. Inf. Sci., vol. 8, no. 1, pp. 107–112, 2014, doi: 10.12785/amis/080112.
K. Reddy and V. Clinton, “Simulating stock prices using geometric Brownian motion: Evidence from Australian companies,†Australas. Accounting, Bus. Financ. J., vol. 10, no. 3, pp. 23–47, 2016, doi: 10.14453/aabfj.v10i3.3.
N. Parungrojrat and A. Kidsom, “Stock Price Forecasting: Geometric Brownian Motion and Monte Carlo Simulation Techniques,†MUT J. Bus. Adm., vol. 16, no. 1, pp. 9–103, 2019.
W. Farida Agustini, I. R. Affianti, and E. R. M. Putri, “Stock price prediction using geometric Brownian motion,†J. Phys. Conf. Ser., vol. 974, no. 1, 2018, doi: 10.1088/1742-6596/974/1/012047.
R. Kumar Si and B. Bishi, “Forecasting Short Term Return Distribution of S&P BSE Stock Index Using Geometric Brownian Motion: An Evidence from Bombay Stock Exchange,†Int. J. Stat. Syst., vol. 15, no. 1, pp. 29–45, 2020, [Online]. Available: http://www.ripublication.com.
R. S. Tsay, Analysis of Financial Time Series: Third Edition. 2010.
S. Journal, A. Statistical, and N. Mar, “The Kolmogorov-Smirnov Test for Goodness of Fit Author ( s ): Frank J . Massey , Jr . Published by : Taylor & Francis , Ltd . on behalf of the American Statistical Association Stable URL : http://www.jstor.org/stable/2280095,†vol. 46, no. 253, pp. 68–78, 2017.
S. Kırbıyık, “Stock price modelling : Theory and Practice,†Masters Degree Thesis, Vrije Univ., 2004.
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