1Department of Data Science, Faculty of Computer Science, Universitas Pembangunan Nasional "Veteran" Jawa Timur, Surabaya, Indonesia
2Department of Information and Communication Systems, Okayama University, Japan
3Data Science Study Program, Faculty of Computer Science, Indonesia
BibTex Citation Data :
@article{JSMO73062, author = {Trimono Trimono and Tresna Fahrudin and Ardia Ardiani}, title = {Prediction Of Loss Risk Investment On The Idx Indonesia: Quantitative Approach With Var And Adj-Es}, journal = {JURNAL STUDI MANAJEMEN ORGANISASI}, volume = {22}, number = {1}, year = {2025}, keywords = {Stock Investment; Loss Risk; Blue Chip; VaR; Adj-ES}, abstract = { Loss is the primary risk associated with any investment. In stock investments, the risk of loss can occur at any time and its magnitude cannot be precisely determined. Improper risk management can negatively impact the investment activities carried out by investors. One way to manage risk effectively and prevent bankruptcy is by estimating the potential future risk. This study aims to predict the risk of loss using the quantitative Value-at-Risk (VaR) model, particularly for stocks listed on IDX Indonesia. VaR has the main advantage of being a simple model that can be applied to various types of financial assets. However, VaR also has a drawback it does not satisfy the subadditivity principle. Therefore, this study also employs the Adjusted-Expected-Shortfall (Adj-ES) model as an improvement to VaR. The VaR and Adj-ES models will be implemented on the stocks AMRT.JK and BBCA.JK. These two stocks are part of the IDX Indonesia 2024 blue chip stocks, with a significant increase in market capitalization. The results show that VaR provides prediction results for the risk of loss in the range of 1.2% - 3.4 for AMRT.JK data, and 1.1 - 3.2% for BBCA.JK data. Referring to the Violation Ratio value, it is known that both VaR and Adj-ES have VR values <1 so it is concluded that the prediction accuracy is very good }, pages = {45--57} doi = {10.14710/jsmo.v22i1.73062}, url = {https://ejournal.undip.ac.id/index.php/smo/article/view/73062} }
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