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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Kubik Jurnal Matematika: MANTIK Teorema: Teori dan Riset Matematika International Journal of Supply Chain Management Eksakta : Berkala Ilmiah Bidang MIPA FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Kumawula: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika KUBIK: Jurnal Publikasi Ilmiah Matematika International Journal of Business, Economics, and Social Development Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Mathematical Sciences and Applications Journal
Betty Subartini
Departemen Matematika, FMIPA, Universitas Padjadjaran
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Comparison of Stock Mutual Fund Price Forecasting Results Using ARIMA and Neural Network Autoregressive Model Sianturi, Sri Novi Elizabeth; Subartini, Betty; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.1001

Abstract

Stock mutual funds gained popularity among the public as an investment alternative due to the convenience they offer, especially for beginner investors who have limited time and investment knowledge. Compared to money market and bond mutual funds, these mutual funds offer higher potential returns but also come with higher risks due to value fluctuations, so forecasting stock mutual fund prices is essential to minimize losses. Since stock mutual fund prices is time series data, this research employs two forecasting models such as Autoregressive Integrated Moving Average (ARIMA) and Neural Network Autoregressive (NNAR). The objective of this research is to determine the best-performing model between ARIMA and NNAR, and compare their forecasting accuracy using the Mean Absolute Percentage Error (MAPE). The data used consists of daily closing prices of stock mutual funds from March 1, 2022, to March 31, 2025, with the criteria that the selected issuers have been operating for more than five years. The results of this research show that the best ARIMA and NNAR for the RNCN are ARIMA([1],1,0) and NNAR(2,2); for TRAM are ARIMA(0,1,[1]) and NNAR(4,1); for SCHRP are ARIMA(0,1,[1]) and NNAR(4,2); for MICB are ARIMA([1],1,0) and NNAR(2,2); and for BNPP are ARIMA([1],1,0) and NNAR(5,1). The MAPE values in the same order are 6.83% and 5.49%; 6.53% and 5.75%; 8.57% and 7.10%; 8.39% and 8.75%; 8.51% and 7.30%. Based on the comparison, NNAR outperformed ARIMA in four out of five mutual funds, with lower MAPE values and also marked by the ARIMA model tend to produce stable or unchanging values over the long term. The results of this research are expected to assist investors in consederating by choosing NNAR model, both in the short and long term, to obtain better stock mutual fund price forecasts.
Investment Portfolio Optimization Using the Mean-Variance Model Based on Holt-Winters Stock Price Forecasting of Food Sector in Indonesia Nurdyah, Himda Anataya; Subartini, Betty; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.1017

Abstract

The importance of the food sector to Indonesia's economy makes it one of the most attractive sectors to consider in an investment portfolio. An optimal portfolio is the best choice for investors among various efficient portfolios, aiming to maximize returns while minimizing risk. Moreover, since investment is inherently associated with fluctuating stock prices, accurate forecasting is necessary to anticipate future stock movements. This study aims to accurately predict stock prices and construct an optimal portfolio consisting of five food sector stocks listed on the Indonesia Stock Exchange, namely DMND, ICBP, HOKI, INDF, and ULTJ. Stock price predictions are generated using the Holt-Winter method, which can identify seasonal patterns and trends from historical data. The predicted stock prices are then used to calculate returns, which serve as the basis for portfolio optimization using the Mean-Variance model. The results show that the Holt-Winter method successfully produces accurate stock price forecasts, with Mean Absolute Percentage Error (MAPE) values for all stocks below 10%. These forecasts are used to calculate returns in the portfolio optimization process. The optimal portfolio composition is determined with the following weight proportions: HOKI (4%), ICBP (18%), ULTJ (21%), DMND (26%), and INDF (30%). This portfolio yields an expected return of 0.0441% and a portfolio variance of 0.0063%, reflecting a balanced trade-off between potential return and risk.
Optimal Stock Portfolio Analysis using Mean-Value at Risk (Mean-VaR) under Arbitrage Pricing Theory (APT) Banowati, Puspa Dwi Ayu; Subartini, Betty; Sukono, Sukono
International Journal of Business, Economics, and Social Development Vol. 5 No. 1 (2024)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i1.584

Abstract

Investing in Sharia-compliant stocks is one of the rapidly growing investment options, making it a potential choice for investors' portfolios. Therefore, investors need to understand how to select an optimal composition of stocks in their portfolio. This research aims to calculate the expected return on Sharia-compliant stocks and determine the optimal portfolio. The data used in this study includes stocks within the Indonesian Sharia Stock Index (ISSI) in the energy and mining sectors from November 1, 2022, to October 30, 2023. The analytical models employed are the Arbitrage Pricing Theory (APT) and Mean-Value at Risk (Mean-VaR). Based on the research findings, seven stocks form the composition of the optimal stock portfolio. These stocks are AKRA, ANTM, PGAS, INCO, INDY, PTBA, and MDKA, with weights of 20.54%, 19.58%, 19.02%, 14.24%, 10.97%, 8.00%, and 7.66%, respectively. The expected return for the investor is 0.13% per day, with a corresponding risk of 0.23%.
Co-Authors - Riaman Adib, Andhita Zahira Agus Santoso Agus Supriatna Agus Supriatna Aisyah Nurul Aini Alfan Azkiya Robbani Amalia, Hana Safrina Annisa Aprillia Annisa Nur Falah Annisa Nur Falah, Annisa Nur Apipah Jahira, Juwita Ary Robayani Asep K Supriatna Asep K Supriatna, Asep K Asri Rula Hanifah Azimah Lisan Robbani Banowati, Puspa Dwi Ayu Budi N. Ruchajana Budi N. Ruchajana, Budi N. Carissa, Katherine Liora Diah Chaerani Dian Nuryani Dini Aulia Dwi Susanti Eddy Djauhari Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Elis Hertini Endang Rusyaman Endang Soeryana Hasbullah Felfin Ulfah Annisa Firdaniza Firdaniza Firdaus, Muhammad Rayhan Ghazali, Puspa Liza Herlina Napitupulu Jeane R. M. D. P Chantique Jumadil Saputra Kankan Parmikanti Muhammad Iqbal Al-Banna Ismail Nahda Nabiilah Novitasari, Ela Nurdyah, Himda Anataya Nursanti Anggriani Nurul Fadilah Nurul Gusriani, Nurul Olivia Anjanette Pamungkas, Abram Chandra Aji Putri Adhira Novalia Putri Chaerunnisa Febryanti Putri, Sherina Anugerah R Wulantini R Wulantini, R Rahmadhisa, Nayra Pavita Rahman, Rezki Aulia Reisnanda, Aldino Riaman . Riaman Riaman Riaman Riaman Riaman Riaman Riaman Riaman, Riaman Risdawati Risdawati Sampath, Sivaperumal Saputra, Jumadil Sianturi, Sri Novi Elizabeth Silvia Wijaya Sisilia Sylviani Sonia . Sukono Sukono Tampubolon, Carlos Naek Tua Tegar Ridwansyah Yeremia Herry Parulian Yeremia Herry Parulian, Yeremia Herry Zahra, Ami Emilia Putri Zakirah, Khalilah Razanah