Prediksi Harga Saham Sektor Perbankan Menggunakan ARIMAX-GARCH dan Estimasi Value at Risk dengan Simulasi Monte Carlo

Arimba, Elsa Amelia Nur (2026) Prediksi Harga Saham Sektor Perbankan Menggunakan ARIMAX-GARCH dan Estimasi Value at Risk dengan Simulasi Monte Carlo. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Ketidakpastian pasar modal Indonesia pada awal tahun 2025 akibat gejolak geopolitik, kebijakan tarif impor Amerika Serikat, dan pelemahan rupiah menyebabkan tingginya volatilitas harga saham, sehingga diperlukan metode peramalan yang akurat. Penelitian ini berfokus pada tiga emiten perbankan berkapitalisasi besar, yaitu BBCA, BBRI, dan BMRI, yang dipilih berdasarkan konsistensinya berada dalam 10 besar emiten dengan kapitalisasi pasar terbesar di BEI. Peramalan dilakukan menggunakan model ARIMAX-GARCH dengan variabel eksogen berupa IHSG, nilai tukar rupiah, dan harga emas global, yang masing-masing merepresentasikan kondisi pasar saham, risiko makroekonomi, dan aset safe haven. Selain itu, penelitian ini juga mengukur tingkat risiko investasi menggunakan metode Value at Risk (VaR) berbasis simulasi Monte Carlo untuk memberikan gambaran potensi kerugian maksimum pada masing-masing saham. Data yang digunakan merupakan data harian dari Januari 2022-Oktober 2025. Hasil penelitian menunjukkan bahwa model prediksi terbaik saham BBCA dan BMRI yaitu ARIMAX(1,1,1)-GARCH(1,1,) dengan masing-masing MAPE 1,017% dan 1,184%. Sedangkan BBRI dengan model terbaik ARIMAX(0,1,1)-GARCH(1,1) dan MAPE sebasar 1,281%. Hasil estimasi VaR dengan simulasi Monte Carlo pada tingkat kepercayaan 95% menunjukkan bahwa BBCA memiliki tingkat risiko terendah sebesar 0,0515%, BBRI sebesar 0,0699%, dan BMRI sebesar 0,0658%. Sehingga, investor disarankan memilih saham BBCA sebagai aset pelindung dengan risiko terendah dan pertumbuhan cukup stabil, BBRI dapat dipilih untuk mengoptimalkan potensi pertumbuhan, serta BMRI dapat dijadikan pilihan untuk investasi jangka panjang.
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The uncertainty of the Indonesian capital market in early 2025 due to geopolitical turmoil, the policy of import tariffs in the United States, and the weakening of the rupiah has caused high volatility in stock prices, so accurate forecasting methods are needed. This research focuses on three large-cap banking issuers, namely BBCA, BBRI, and BMRI, which were selected based on their consistency in being in the top 10 issuers with the largest market capitalization on the IDX. The forecasting was carried out using the ARIMAX-GARCH model with exogenous variables in the form of JCI, rupiah exchange rate, and global gold price, each of which represents stock market conditions, macroeconomic risks, and safe haven assets. In addition, this study also measures the level of investment risk using the Monte Carlo simulation-based Value at Risk (VaR) method to provide an overview of the maximum potential loss in each stock. The data used is daily data from January 2022-October 2025. The results of the study show that the best prediction model for BBCA and BMRI stocks is ARIMAX(1,1,1)-GARCH(1,1,) with MAPE of 1.017% and 1.184%, respectively. Meanwhile, BBRI with the best models ARIMAX(0,1,1)-GARCH(1,1) and MAPE is 1.281%. The results of the VaR estimate with Monte Carlo simulation at a confidence level of 95% showed that BBCA had the lowest risk level of 0.0515%, BBRI of 0.0699%, and BMRI of 0.0658%. Thus, investors are advised to choose BBCA shares as a protective asset with the lowest risk and fairly stable growth, BBRI can be chosen to optimize growth potential, and BMRI can be used as an option for long-term investment.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	ARIMAX-GARCH, BBCA, BBRI, BMRI, Monte Carlo Simulation, VaR, ARIMAX-GARCH, BBCA, BBRI, BMRI, Monte Carlo Simulation, VaR
Subjects:	H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HG Finance > HG4915 Stocks--Prices
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Elsa Amelia Nur Arimba
Date Deposited:	03 Aug 2026 08:40
Last Modified:	03 Aug 2026 08:40
URI:	http://repository.its.ac.id/id/eprint/141443

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