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All Journal Operations Research: International Conference Series International Journal of Quantitative Research and Modeling
Laila, Aliffatul
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Mathematics Physics

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Comparison of Islamic and Conventional Bank Stock Portfolio Performance Using the Markowitz Model: Risk and Return Analysis on Four Selected Issuers Laila, Aliffatul; Janitha, Asrie Putri
International Journal of Quantitative Research and Modeling Vol. 6 No. 3 (2025): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

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Abstract

This study aims to compare the performance of Islamic and conventional bank stock portfolios in Indonesia using the Markowitz Model approach that focuses on return and risk optimization. The object of research includes four banking issuers, namely BBCA and BBNI (conventional), and BRIS and BTPS (sharia), with daily closing price data during the period March 2020 to March 2021. Calculations were made on expected return, risk (standard deviation), sharpe ratio, and optimal portfolio composition. The results show that the Islamic stock portfolio has a higher expected return (0.009385) than the conventional portfolio (0.001652), but is accompanied by greater risk. Nevertheless, the efficiency of the Islamic portfolio remains competitive based on the sharpe ratio indicator and the ratio of return to variance. The optimal composition in the Islamic portfolio is dominated by BTPS stocks (68.69%), while in the conventional portfolio it is dominated by BBNI stocks (62.19%). These findings suggest that an Islamic bank stock portfolio can be an investment alternative that is not only ethical, but also financially superior in terms of risk and return.
Bankruptcy Probability Analysis of PT XYZ Using a Heavy-Tail (Pareto) Discrete Surplus Model Laila, Aliffatul; Janitha, Asrie Putri
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.420

Abstract

The insurance industry plays a strategic role in maintaining societal financial stability by providing protection mechanisms against unforeseen risks. However, the risk of bankruptcy remains a real threat when policyholder claims exceed the company's reserve funds and collected premiums. This necessitates a quantitative approach capable of projecting bankruptcy probability more accurately. This study is designed to analyze the bankruptcy probability of PT XYZ by utilizing a discrete surplus model based on the heavy-tail Pareto distribution. This model was selected due to its characteristics, which can effectively represent large, infrequent claims that nonetheless have a significant impact on the company's financial condition. The research data will be sourced from the company's financial reports and used in the bankruptcy probability modeling process employing the Pareto distribution approach. This research is expected to provide a theoretical contribution by enriching actuarial literature, particularly concerning the application of heavy-tail surplus models in bankruptcy risk analysis. It also aims to offer practical benefits for insurance companies in designing more comprehensive risk management strategies. Furthermore, the study's findings are hoped to provide valuable input for regulators in strengthening policyholder protection policies and supporting the stability of the national insurance industry. Keywords: Bankruptcy, Insurance, Surplus model, Heavy-tail, Pareto Distribution
Co-Authors Janitha, Asrie Putri