The Non-Seasonal Holt-Winters Method for Forecasting Stock Price Returns of Companies Affected by BDS Action
Article Sidebar
Page Numbers:
8-26
Digital Object Identifier:
10.58578/mjms.v2i1.2673
Viewed: 838 times
Downloaded: 482 times
LYAS Publisher cordially invites qualified professionals to serve as Editors or Reviewers. Your expertise will make an important contribution to maintaining and strengthening the academic quality of our publications. Interested applicants are kindly requested to complete the application form at the following link: Editors & Reviewers
Please feel free to contact us if you need any further information about the submission process or if you have any additional questions.
Authors:
Anggun Yuliarum Qur'ani1*, Chandra Sari Widyaningrum2 
Copyright :
Authors retain copyright and grant the journal right of first publication.
Main Article Content
Abstract
The non-seasonal Holt-Winters method is one of the methods of smoothing theory. This method can be implemented on time series data that does not have a seasonal component. In this study, this method is used to forecast the stock price returns of companies affected by the Boycott, Divestment, and Sanctions (BDS) action. Forecasting gets very good results that can be seen from the MAPE value of modeling the six stocks affiliated with Israel that continue to carry out Zionism against Palestine is not more than 10%. This method can also accommodate the limitations of existing data while still obtaining good forecasting results. In addition, the use of several transformations of stock price returns in this case is very useful in modeling to obtain appropriate error assumptions. The forecasting results of the model formed as a whole follow the trend in the stock price of each company. To produce good forecasting results using this method, it is recommended to do forecasting in the short term. The forecasting results show that of the six company stocks, almost all of them experienced a decrease in stock price returns. Only one stock of PT Map Boga Adiperkasa Tbk has increased. This also illustrates that the BDS action influences on these companies.
Downloads
Article Details
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Abdillah, T. (2023). Penerapan Algoritma Holt-Winters Exponential Smoothing Untuk Prediksi Produksi Kelapa Sawit (Studi Kasus: PT Perkebunan Sumatera Utara Perseroda) [Skripsi]. Universitas Mercu Buana Jakarta.
Boyadzhiev, K. N. (2005). A series transformation formula and related polynomials. International Journal of Mathematics and Mathematical Sciences, 2005(23), 3849–3866. https://doi.org/10.1155/IJMMS.2005.3849
Cetin, B., & Yavuz, I. (2021). Comparison of forecast accuracy of Ata and exponential smoothing. Journal of Applied Statistics, 48(13–15), 2580–2590. https://doi.org/10.1080/02664763.2020.1803813
Chai, T., & Draxler, R. R. (2014). Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature. Geoscientific Model Development, 7(3), 1247–1250. https://doi.org/10.5194/gmd-7-1247-2014
CNBC Indonesia, R. (2024, January 14). 100 Hari Perang Gaza: 23.843 Korban Tewas, Konflik Meluas ke Yaman [News]. CNBN Indonesia. https://www.cnbcindonesia.com/news/20240114001607-4-505405/100-hari-perang-gaza-23843-korban-tewas-konflik-meluas-ke-yaman
Dettling, D. M. (2021). Statistical Analysis of Financial Data. Zurich University of Applied Sciences.
Dickey, D. A., & A. Fuller, W. (1979). Distributions of the Estimators for Autoregressive Time Series with a Unit Root. Journal of American Statistical Association, 74(366), 427–481.
Dickey, D. A., & Fuller, W. A. (1981). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Econometrica, 49(4), 1057–1072.
Diebold, F. X. (2017). In Economics, Business, Finance and Beyond. University of Pennsylvania.
Djakaria, I., & Saleh, S. E. (2021). Covid-19 forecast using Holt-Winters exponential smoothing. Journal of Physics: Conference Series, 1882(1), 012033. https://doi.org/10.1088/1742-6596/1882/1/012033
Fattore, M. (2019). Holt-Winters methods. Università degli Studi di Milano-Bicocca. https://www.unimib.it/sites/default/files/allegati/17-10-2019/4_-_holt-winters.pdf
Glynn, J., Perera, N., & Verma, R. (2007). Unit Root Tests and Structural Breaks: A Survey with Applications. Revista De M ́ Etodos Cuantitativos Para La Econom ́ia Y La Empresa, 3, 63–79.
Hanusz, Z., Tarasinska, J., & Zielinski, W. (2016). Shapiro–Wilk Test With Known Mean. REVSTAT – Statistical Journal, 14(1), 89–100.
Hecht, M., & Zitzmann, S. (2021). Sample Size Recommendations for Continuous-Time Models: Compensating Shorter Time Series with Larger Numbers of Persons and Vice Versa. Structural Equation Modeling: A Multidisciplinary Journal, 28(2), 229–236. https://doi.org/10.1080/10705511.2020.1779069
Hyndman, R., Athanasopoulos, G., Bergmeir, C., Caceres, G., Chhay, L., Kuroptev, K., O’Hara-Wild, M., Petropoulos, F., Razbash, S., Wang, E., & Yasmeen, F. (2023). forecast: Forecasting Functions for Time Series and Linear Models. CRAN R.
IMC News.id. (2023, November 27). Saham 6 Perusahaan ini Rontok Berjamaah, Gerakan Boikot Produk ‘Berbau’ Israel Berhasil [Internasional]. IMC News.Id. https://imcnews.id/read/2023/11/27/22503/saham-6-perusahaan-ini-rontok-berjamaah-gerakan-boikot-produk-%E2%80%98berbau%E2%80%99-israel-berhasil
Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303.
Luo, J., Chen, W., Ray, J., & Li, J. (2022). Short-Term Polar Motion Forecast Based on the Holt-Winters Algorithm and Angular Momenta of Global Surficial Geophysical Fluids. Surveys in Geophysics, 43(6), 1929–1945. https://doi.org/10.1007/s10712-022-09733-0
Mawaddah, S. (2023). Perbandingan Metode Holt Winters Exponential Smoothing Dan Holt Weight Exponential Moving Average Dalam Peramalan Harga Cabai Rawit Di Kabupaten Purbalingga Kabupaten Purbalingga [Skripsi]. Universitas Negeri Jakarta.
Muhamad, S. V. (2023). Konflik Palestina (Hamas) – Israel. Pusat Analisis Keparlemenan Badan Keahlian DPR RI, XV(20/II/Pusaka), 6–10.
Norman L., J., Kots, S., & Balakrishnan, N. (1994). Exponential Distributions. In Continuous Univariate Distributions,: Vol. I and II. John Wiley and Sons.
Rao, S. (2022). A course in Time Series Analysis. Texas A&M University.
Richards, R. (2005). Unit Root Tests. University of Washington. https://faculty.washington.edu/ezivot/econ584/notes/unitroot.pdf
Takahasi, H., & Mori, M. (1973). Double exponential formulas for numerical integration. Publications of the Research Institute for Mathematical Sciences, 9(3), 721–741. https://doi.org/10.2977/prims/1195192451
Trapletti, A., Hornik, K., & LeBaron, B. (2023). Time Series Analysis and Computational Finance. CRAN R. https://cran.r-project.org/web/packages/tseries/tseries.pdf
Yahoo Finance. (2024, January 16). Yahoo Finance Profile. https://finance.yahoo.com/