Main Article Content
Abstract
Purpose – This study aims to predict the weekly stock price of Spotify Technology SA (SPOT) using Support Vector Regression (SVR) and to evaluate investment feasibility based on Net Present Value (NPV), Internal Rate of Return (IRR), Sharpe Ratio, and Sortino Ratio.
Methods – Weekly stock price data from October 2022 to May 2026 (190 observations) were analyzed using SVR with lag selection based on PACF and kernel optimization through two-stage grid search. Investment feasibility was evaluated using NPV, IRR, Sharpe Ratio, and Sortin o Ratio.
Findings – The linear kernel SVR achieved the best performance with MAPE of 5.44% (training) and 4.61% (testing). The NPV was positive at USD 19,685.86. However, the IRR of 1.197% per week, Sharpe Ratio of 0.3703, and Sortino Ratio of 17.77 consistently indicate that Spotify stock during the prediction period is not financially viable for investment.
Implication – The findings emphasize the importance of combining return- and risk-based measures when evaluating investment feasibility, particularly for high-volatility assets.
Originality – Unlike prior studies that focus mainly on forecasting accuracy, this study integrates SVR-based prediction and investment feasibility analysis using NPV, IRR, Sharpe, and Sortino ratios within within a unified framework.
Abstrak
Tujuan – Penelitian ini bertujuan untuk memprediksi harga saham mingguan Spotify Technology SA (SPOT) menggunakan metode Support Vector Regression (SVR) serta mengevaluasi kelayakan investasi berdasarkan Net Present Value (NPV), Internal Rate of Return (IRR), Sharpe Ratio, dan Sortino Ratio.
Metode – Data harga saham mingguan periode Oktober 2022 hingga Mei 2026 (190 observasi) dianalisis menggunakan SVR dengan pemilihan lag berdasarkan PACF dan optimasi kernel melalui grid search dua tahap.
Temuan – Kernel linear SVR menghasilkan performa terbaik dengan MAPE sebesar 5,44% pada data pelatihan dan 4,61% pada data pengujian. NPV bernilai positif sebesar USD 19.685,86. Namun, IRR sebesar 1,197% per minggu, Sharpe Ratio sebesar 0,3703, dan Sortino Ratio sebesar 17,77 secara konsisten menunjukkan bahwa saham Spotify pada periode prediksi tidak layak secara finansial untuk diinvestasikan.
Implikasi – Temuan penelitian menekankan pentingnya mengombinasikan indikator berbasis imbal hasil dan risiko dalam mengevaluasi kelayakan investasi, khususnya pada aset dengan volatilitas tinggi.
Orisinalitas – Berbeda dengan penelitian sebelumnya yang terutama berfokus pada akurasi peramalan, penelitian ini mengintegrasikan prediksi berbasis SVR dan analisis kelayakan investasi menggunakan NPV, IRR, Sharpe Ratio, dan Sortino Ratio dalam satu kerangka yang terpadu.
Keywords
Article Details
Copyright (c) 2026 M. Fariz Fadillah Mardianto, Ferissa Maulida Ismi, Anggita Nariswari, Amelia Fatihah, Idrus Syahzaqi

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
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- Osborne, M. J. (2010). A resolution to the NPV–IRR debate? The Quarterly Review of Economics and Finance, 50(2), 234–239. https://doi.org/10.1016/J.QREF.2010.01.002
- Oukhouya, H., & Khalid, E. (2023). A comparative study of ARIMA, SVMs, and LSTM models in forecasting the Moroccan stock market. International Journal of Simulation and Process Modelling, 20, 125–143. https://doi.org/10.1504/IJSPM.2023.136481
- Ruliana, R., Rais, Z., Marni, M., & Ahmar, A. S. (2024). Implementation of the Support Vector Regression (SVR) Method in Inflation Prediction in Makassar City. ARRUS Journal of Mathematics and Applied Science, 4(1 SE-Articles), 28–35. https://doi.org/10.35877/mathscience2608
- Sari, A., Zuleika, T., Mardianto, M., & Pusporani, E. (2025). Application of Support Vector Regression in Time Series Analysis of Dior Stock Prices. Zeta - Math Journal, 10, 51–60. https://doi.org/10.31102/zeta.2025.10.1.51-60
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- Sortino, F. A., & van der Meer, R. (1991). Downside risk: Capturing what’s at stake in investment situations. Journal of Portfolio Management, 17(4), 27–31. https://doi.org/10.3905/JPM.1991.409343
- Srivastava, D., & Mazhar, S. (2018). Comparative Analysis of Sharpe and Sortino Ratio with reference to Top Ten Banking and Finance Sector Mutual Funds. International Journal of Management Studies, V, 93. https://doi.org/10.18843/ijms/v5i4(2)/10
- Supriyanto, Y., Sugiyanto, & Suripto. (2024). Determinan Kinerja Fundamental Bank, Kinerja Fundamental Ekonomi Makro Dan Aksi Korporasi Terhadap Harga Saham. Jurnal Akuntansi Dan Bisnis Indonesia (JABSI), 5(2), 171–185.
- Wahidin, A. J., & Putra, R. M. S. (2025). Analisis Keputusan Dalam Menentukan Cryptocurrency Terbaik Menggunakan Metode Net Present Value (NPV). Jurnal Komputer Dan Sistem Informasi, 2, 11–16. https://doi.org/10.66865/nd9fsm48
- Wahyudi, R., Annas, S., & Rais, Z. (2023). Analisis Support Vector Regression (Svr) Untuk Meramalkan Indeks Kualitas Udara Di Kota Makassar. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 5(3), 104–117. https://doi.org/10.35580/variansiunm107
References
Ahmad, R., Rani, S. C., Pribadi, C. A., Sabilla, R. P., Fatimah, R. S. S., Tirta, M. A. D., Rahmawati, N., Dewi, F. R., & Sinaga, A. R. (2025). Analisis Kelayakan Investasi Usaha Laga Lagi Thrift Menggunakan Pendekatan Capital Budgeting: Studi Kasus Metode Payback Period, NPV, DAN IRR. Jurnal Akuntansi, Manajemen Dan Ekonomi, 4(1 SE-), Page 25-35. https://doi.org/10.56248/jamane.v4i1.123
Beniwal, M., Singh, A., & Kumar, N. (2023). Forecasting long-term stock prices of global indices: A forward-validating Genetic Algorithm optimization approach for Support Vector Regression. Applied Soft Computing, 145, 110566. https://doi.org/10.1016/J.ASOC.2023.110566
Cahyono, R. E., Sugiono, J. P., & Tjandra, S. (2019). Analisis Kinerja Metode Support Vector Regression (SVR) dalam Memprediksi Indeks Harga Konsumen. JTIM : Jurnal Teknologi Informasi Dan Multimedia, 1, 106–116. https://doi.org/10.35746/jtim.v1i2.22
Fanani, Z. A. (2021). Analisis Kelayakan Biaya (Benefit Cost Analysis) Dalam Pembangunan Rusun Penjaringan Dengan Metode Npv, Irr, Pp, Bcr Menggunakan Software Investment Evaluation. Https://Jim.Unindra.Ac.Id/Index.Php/Sijie/Article/View/4191/630.
Henrique, B. M., Sobreiro, V. A., & Kimura, H. (2019). Literature review: Machine learning techniques applied to financial market prediction. Expert Systems with Applications, 124, 226–251. https://doi.org/https://doi.org/10.1016/j.eswa.2019.01.012
Jiang, W. (2021). Applications of deep learning in stock market prediction: Recent progress. Expert Systems with Applications, 184, 115537. https://doi.org/https://doi.org/10.1016/j.eswa.2021.115537
Lin, J. (2023). A comparative study on the application of NPV and IRR in financial market investment decision. Academic Journal of Business & Management, 5(4), 51–54. https://doi.org/10.25236/AJBM.2023.050409
Nugroho, F. A. R., & Margana, R. R. (2024). Analisis Kelayakan Investasi Pada Usaha Pertanian Sayur Menggunakan Metode NPV, IRR dan PP di Kampung Pojok Desa Jaya Mekar Kecamatan Padalarang Kabupaten Bandung Barat. JURNAL SYNTAX IMPERATIF : Jurnal Ilmu Sosial Dan Pendidikan, 5(4 SE-Articles), 698–706. https://doi.org/10.36418/syntaximperatif.v5i4.465
Osborne, M. J. (2010). A resolution to the NPV–IRR debate? The Quarterly Review of Economics and Finance, 50(2), 234–239. https://doi.org/10.1016/J.QREF.2010.01.002
Oukhouya, H., & Khalid, E. (2023). A comparative study of ARIMA, SVMs, and LSTM models in forecasting the Moroccan stock market. International Journal of Simulation and Process Modelling, 20, 125–143. https://doi.org/10.1504/IJSPM.2023.136481
Ruliana, R., Rais, Z., Marni, M., & Ahmar, A. S. (2024). Implementation of the Support Vector Regression (SVR) Method in Inflation Prediction in Makassar City. ARRUS Journal of Mathematics and Applied Science, 4(1 SE-Articles), 28–35. https://doi.org/10.35877/mathscience2608
Sari, A., Zuleika, T., Mardianto, M., & Pusporani, E. (2025). Application of Support Vector Regression in Time Series Analysis of Dior Stock Prices. Zeta - Math Journal, 10, 51–60. https://doi.org/10.31102/zeta.2025.10.1.51-60
Sheng, T. (2023). Comparative Analysis of NPV and IRR in Investment Decision Making. Highlights in Business, Economics and Management, 21, 592–597. https://doi.org/10.54097/HBEM.V21I.14695
Sortino, F. A., & van der Meer, R. (1991). Downside risk: Capturing what’s at stake in investment situations. Journal of Portfolio Management, 17(4), 27–31. https://doi.org/10.3905/JPM.1991.409343
Srivastava, D., & Mazhar, S. (2018). Comparative Analysis of Sharpe and Sortino Ratio with reference to Top Ten Banking and Finance Sector Mutual Funds. International Journal of Management Studies, V, 93. https://doi.org/10.18843/ijms/v5i4(2)/10
Supriyanto, Y., Sugiyanto, & Suripto. (2024). Determinan Kinerja Fundamental Bank, Kinerja Fundamental Ekonomi Makro Dan Aksi Korporasi Terhadap Harga Saham. Jurnal Akuntansi Dan Bisnis Indonesia (JABSI), 5(2), 171–185.
Wahidin, A. J., & Putra, R. M. S. (2025). Analisis Keputusan Dalam Menentukan Cryptocurrency Terbaik Menggunakan Metode Net Present Value (NPV). Jurnal Komputer Dan Sistem Informasi, 2, 11–16. https://doi.org/10.66865/nd9fsm48
Wahyudi, R., Annas, S., & Rais, Z. (2023). Analisis Support Vector Regression (Svr) Untuk Meramalkan Indeks Kualitas Udara Di Kota Makassar. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 5(3), 104–117. https://doi.org/10.35580/variansiunm107