FINANCIAL SECTOR STOCK PRICE FORECASTING AND LOSS RISK USING THE ARIMAX AND VALUE-AT-RISK (VAR) METHODS

Aulia, Amanda (2025) FINANCIAL SECTOR STOCK PRICE FORECASTING AND LOSS RISK USING THE ARIMAX AND VALUE-AT-RISK (VAR) METHODS. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Stock price fluctuations are one of the key phenomena influencing investment decision-making in the capital market. The banking sector, as a vital component of Indonesia’s financial system, often exhibits stock price volatility caused by changes in macroeconomic conditions such as foreign exchange rates. The dynamic movement of PT Bank Central Asia Tbk (BBCA) stock reflects its high sensitivity to external factors, creating uncertainty for investors in estimating potential returns and risks. The main issue addressed in this research is how to construct a forecasting model that effectively captures the relationship between stock prices and relevant external variables, while simultaneously measuring potential investment risk comprehensively. To address this problem, this study employs the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model for stock price forecasting and the Value-at-Risk (VaR) method with the historical simulation approach to estimate potential losses. The data used include BBCA stock prices and the exchange rates of USD/IDR and SGD/IDR from January 2019 to September 2024. The results indicate that the ARIMAX(3,1,3) model performs best, with an Akaike Information Criterion (AIC) value of 16536,9595 and a Mean Absolute Percentage Error (MAPE) of 2,19%, classified as highly accurate. Meanwhile, the VaR analysis estimates a maximum potential loss of Rp2.038 for a single asset value of Rp1.000.000 at a 95% confidence level. In terms of urgency, this study is significant in assisting investors to understand the behavior of banking stocks under volatile market conditions, while providing a data-driven predictive approach for more reliable forecasting. From a research gap perspective, this study integrates ARIMAX and VaR methods simultaneously to analyze both forecasting and risk, which are rarely applied together in similar research within the Indonesian capital market context. Moreover, the development of a web-based Graphical User Interface (GUI) serves as an additional innovation that enhances analytical efficiency and interactive visualization. Overall, this research aims to provide both empirical and practical contributions to improving the accuracy of stock price forecasting and investment risk management, supporting more rational and data-informed decision-making in the financial sector, particularly in banking.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Trimono, Trimono	NIDN0008099501	trimono.stat@upnjatim.ac.id
Thesis advisor	Hindrayani, Kartika Maulida	NIDN0009099205	kartika.maulida.ds@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics > QA76.6 Computer Programming

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

amanda aulia

Date Deposited:

05 Dec 2025 08:37

Last Modified:

05 Dec 2025 08:37

URI:

https://repository.upnjatim.ac.id/id/eprint/48056