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Andik Adi Suryanto
Universitas PGRI Ronggolawe
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Journal : Academia Open

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Hybrid Transformer-LSTM for Stock Price Prediction with Monte Carlo Testing of Loss Levels Saputra, David Andris Rizky; Muqtadir, Asfan; Suryanto, Andik Adi
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13521

Abstract

General Background: Stock price prediction is a complex problem due to the non-linear, stochastic, and volatile characteristics of financial markets. Specific Background: Advanced deep learning approaches such as Long Short-Term Memory (LSTM) and Transformer architectures have been applied to capture sequential patterns and global dependencies in time-series financial data. Knowledge Gap: However, existing approaches often lack integration between accurate forecasting and quantitative risk measurement within a unified framework. Aims: This study proposes a Hybrid Transformer–LSTM model integrated with Monte Carlo simulation to provide both precise stock price prediction and risk evaluation. Results: Using historical daily stock price data of BMRI from March 2013 to March 2025 and incorporating technical indicators such as RSI and moving averages, the model achieved a Mean Absolute Percentage Error of 4.13% and a Mean Absolute Error of 246.35 Rupiah. Monte Carlo-based Value at Risk at a 99% confidence level estimated a potential maximum loss of 5.35%. Novelty: The study combines sequential learning, attention mechanisms, and probabilistic simulation in a single framework linking prediction accuracy with risk quantification. Implications: The proposed approach provides a comprehensive analytical basis for supporting investment decision-making through reliable forecasting and measurable downside risk estimation. Highlights : Combined deep learning architecture produces low forecasting error on long-term historical data Probabilistic simulation quantifies maximum potential loss under high confidence level Integrated framework links predictive modeling with measurable investment risk Keywords: Hybrid Transformer LSTM, Stock Price Prediction, Monte Carlo Value at Risk
Co-Authors Abdullah Nur Huda Adityo Nugroho, Adityo Akmalul Mu’minin Al Mubarok, Bagus Alam, Sitti Nur Alfa Nurfahma Rosalita Alfia Nurlifa Alfian Nurlifa Alfian Nurlifa Alfianisa Hanny Saputri Amaluddin Arifia Amaludin Arifia Amaludin Arifia Amin Masnun Ammar Ma'ruf Andri Tri Setiawan Arifia, Amaludin Arina Rosyida Aris Wijayanti Aris Wijayanti Asfan Muqtadir Asfan Muqtadir Asfan Muqtadir Asfan Muqtadir Azifatin Ni'ayah Bangkit Setyawan, Dany Meiko Bowo, Herry Dewi, Lestari Rozita Dito, Himawan Pramu Diva Elydiya Yahya Dodik Jihar Ananta Dwi Kurnia Basuki Dwi Yulianto Eko Prayudi Yustisio Farkhan, Muhamad Farir Fitroh Amaluddin Fitroh Amaluddin Fitroh Amaluddin Fitroh Amaludin Ghozali, Daniel Reredo Ahmad Haryoko, Andy Heru Prastyo Ihda Maulidia Nurul Farida Imron Rosyidi, Imron Iwan Adhicandra Karya Suhada Kholid Fathoni Kraugusteeliana Kraugusteeliana Krishna Tri Sanjaya Luluk Purwanti M.Farid Musthofa Mahendra Dodik Sugiyanto Marita Ika Joesidawati Mar’atus Sholihah Mellynda Oktaviana Miftahurrohman Mochamad Zaenal Fanani Nafisah, Jauharotun Nia Maulina Ridiani Nur Suci Rahayu Nurul Hidayah Prakoso, Adityo Dwi Puspitaningrum, Fitria Putra, Muharrom Yoga Putri Milenia Putri, Layla Ayu Mustika Rifta Dewi Fortuna Rika Harnita Ririn Safitri Rochman, Apriatur Sahla Saqilla Saputra, David Andris Rizky Saputri, Alfianisa Sari, Fitria Atika Sarofah, Maratus Sasmita, Niken Diah Siti Nurjanah SITI RACHMAWATI Siti Rachmawati Siti Rachmawati Sitti Nur Alam SUPRAPTO Suprapto Suprapto Suwarsih Suwarsih Thoyyib Mau lana Muhtadin Tsalis Rahmawati Uswatun Chasanah Wahyu Candra, Moh. Wenda, Alex Widjaja, Warkianto Wijaya, Hamid Yuliana, Nian Yulistyadi Firman Dwi P.