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All Journal International Journal of Business, Economics, and Social Development International Journal of Quantitative Research and Modeling
Ayyinah Nur Bayyinah
Padjadjaran University, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Social Sciences

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Investment Portfolio Optimization Using Genetic Algorithm on Infrastructure Sector Stocks Based on the Single Index Model Ayyinah Nur Bayyinah; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.977

Abstract

Investment is a strategic step in managing assets to gain profits in the future by allocating some funds in the present. However, behind the promising potential returns, investment also contains risks that cannot be ignored. One way to reduce the level of risk in investing is to implement a portfolio diversification strategy, which is to form an optimal portfolio by allocating investments to various stocks. This study aims to identify the stocks that form the optimal portfolio, determine the optimal weight of each stock, and calculate the expected return and risk of the portfolio. The portfolio optimization process is carried out using Genetic Algorithm, with the calculation of expected return and risk using the Single Index Model (SIM) approach. The data used includes data on stocks in the infrastructure sector for the period July 1, 2023 to June 30, 2024. The results showed that there were six stocks selected in forming the optimal portfolio with the weight of each stock: PGEO 15.0023%, ISAT 32.1522%, GMFI 4.7822%, EXCL 15.3236%, JSMR 29.7379, and OASA 3.0018%. This optimal portfolio provides an expected return of 0.1167% with a portfolio risk of 0.0152%.
Analysis of Financial Distress in Telecommunication Companies in Indonesia Using the Ohlson O-Score and Zmijewski Methods Ayyinah Nur Bayyinah
International Journal of Business, Economics, and Social Development Vol. 6 No. 1 (2025): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.875

Abstract

Currently, major telecommunication sub-sector companies in Indonesia are experiencing rapid growth and have become dominant players in the market. However, not all telecommunication companies are profitable, as some dominant subsidiaries have experienced declining profits or losses, potentially leading to financial distress. Financial distress is a condition where a company is unable to meet its current obligations, such as trade payables, tax liabilities, and short-term debts. This study aims to analyze and evaluate the accuracy of the Ohlson O-Score and Zmijewski methods in detecting financial distress in telecommunication companies in Indonesia. The data used in this study are historical financial data from several telecommunication companies listed on the Indonesia Stock Exchange. The results show that the Ohlson O-Score is effective in early detection of potential financial distress, while the Zmijewski method is more effective in evaluating companies already in critical financial conditions.
Co-Authors Riaman Riaman Sukono Sukono