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All Journal International Journal of Global Operations Research
Helena, Putri Zahra
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Value At Risk (VAR) Analysis using Historical and Monte Carlo Methods in Stock Prices of Bank CIMB Niaga, BSI, BJB, Bank Mega, and Bank Bukopin Helena, Putri Zahra; Puspitasari, Laras Dwi
International Journal of Global Operations Research Vol. 5 No. 3 (2024): International Journal of Global Operations Research (IJGOR), August 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i3.320

Abstract

In daily life and business, risk is unavoidable. Therefore, various ways can be applied to predict and overcome risks. One type of risk that needs to be anticipated especially in the business world is investment risk. Thus, Value at Risk (VaR) is an important tool to predict and anticipate investment risk. This study aims to determine the results of the Value at Risk (VaR) value in the bank sub-sector stock price using the historical simulation method and Monte Carlo simulation for the period 2020-2023. The data used is secondary data sourced from www.yahoo.finance.com which are companies whose stocks are listed on the Indonesia Stock Exchange (IDX) and included in the Indonesia Stock Exchange (IDX). Sampling was carried out by taking 5 bank companies, namely Bank Umum Koperasi Indonesia (BBKB), Bank Pembangunan Daerah Jawa Barat dan Banten (BJBR), Bank MEGA (MEGA), Bank Syariah Indonesia (BRIS), dan Bank CIMB Niaga (BNGA). From the results of the Value at Risk (VaR) value analysis using the historical simulation method and the Monte Carlo simulation method, it is obtained that the company that has the highest VaR risk level is Bank Syariah Indonesia (BRIS).
Bankruptcy Prediction Analysis of Life Insurance Companies Using Altman Z-Score dan Ohlson O-Score Methods Bayyinah, Ayyinah Nur; Helena, Putri Zahra
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.335

Abstract

Life insurance is one of the non-bank industries that offers guarantees to overcome risks. In its implementation, life insurance companies need to maintain the survival of the company in the midst of increasing economic competition so that they don't face the threat of bankruptcy. Bankruptcy itself is a legal status of a certain entity or company that cannot pay its debts to creditors and the company's operations cannot be continued due to lack of funds. This study aims to compare the accuracy of the Altman Z-Score and Ohlson O-Score methods in predicting the bankruptcy of life insurance companies in Indonesia, such as PT Axa Financial Indonesia, PT Taspen Life, Asuransi Jiwa Bersama (AJB) Bumiputera 1912, PT Avrist Assurance, and PT Reliance Life Insurance Indonesia. The data used in this study is secondary data in the form of financial statements of life insurance companies taken from the official website of the relevant company. The results showed that the comparison between the two models revealed that the Altman method is better in predicting company bankruptcy. This is because the Altman method has a more detailed classification of conditions compared to the Ohlson method.
Co-Authors Bayyinah, Ayyinah Nur Puspitasari, Laras Dwi