Membangun Portofolio Optimal dengan Robust Optimization dan Altman Z-Score sebagai Indikator Risiko

Zahro, Andien Maghfirotus (2025) Membangun Portofolio Optimal dengan Robust Optimization dan Altman Z-Score sebagai Indikator Risiko. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam investasi, pengelolaan risiko menjadi salah satu hal yang penting untuk dilakukan, terutama dalam menghadapi ketidakpastian pasar. Untuk membantu investor dalam mengevaluasi risiko dan menentukan strategi investasi, Altman Z-Score dapat digunakan sebagai salah satu alat untuk memprediksi kebangkrutan perusahaan. Selain melalui analisis kebangkrutan, strategi investasi yang lain yaitu dengan mempertimbangkan besar risiko dalam pemilihan proporsi portofolio dapat dilakukan. Model Mean Variance Optimization (MVO) oleh Markowitz merupakan salah satu model optimasi portofolio yang banyak digunakan. Namun, model tersebut memiliki kelemahan yaitu sensitif dengan perubahan kecil atau ketidakpastian parameter seperti return dan kovarian. Oleh karena itu, diperlukan model robust optimization dengan uncertainty (ketidakpastian) data sebagai parameter input. Uncertainty set ini bisa didapatkan salah satunya dari metode moving window. Pendekatan ini dapat diterapkan bagi sektor batu bara yang saat ini sedang menghadapi tantangan besar seiring dengan transisi global menuju clean energy sehingga berdampak pada penurunan harga sahamnya. Pada Tugas Akhir didapatkan hasil bahwa Altman Z-Score dapat digunakan sebagai prediksi kebangkrutan perusahaan dengan menghitung beberapa rasio keuangan. Selanjutnya, dibentuk portofolio optimal melalui robust optimization sebagai permasalahan QP dan SOCP dengan metode moving window untuk membentuk himpunan ketidakpastiannya. Didapatkan hasil bahwa terdapat hubungan antara implementasi Altman Z-Score dengan risiko investasi pada kedua model, baik MVO maupun robust.
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In investment, risk management is one of the important thing to do, especially to address market uncertainty. To assist investors in assessing risks and determining investment strategies, the Altman Z-Score can be used as a tool to predict company’s bankruptcy. In addition to bankruptcy analysis, another investment strategy is to considering the level of risk in determining portfolio allocation. The Mean Variance Optimization (MVO) model by Markowitz is one of the widely used portfolio optimization models. However, this model has a weakness, as it is sensitive to minor changes or uncertainties in parameters such as returns and covariances. Therefore, a robust optimization model that accounts for data uncertainty as input parameters is needed. The uncertainty set can be obtained using methods such as the moving window. The coal industry is currently facing significant challenges because of global transition toward clean energy. The decline in coal usage will inevitably impact coal’s stock prices. Uncertainty about the future of the coal industry makes investors more cautious, particularly when evaluating potential risks and the stability of their investments. In this f inal project, it was found that the Altman Z-Score can be used to predict company’s bankruptcy by calculating several financial ratios. Subsequently, an optimal portfolio was constructed using robust optimization formulated as a Quadratic Programming (QP) and Second-Order Cone Programming (SOCP) problem, applying a moving window approach to define the uncertainty set. This approach can be applied to the coal sector, which is currently facing significant challenges due to the global transition toward clean energy, resulting in a decline in its stock prices. The results indicate that the Altman Z-Score is effective in predicting the company’s bankruptcy. Furthermore, the findings reveal a relationship between the implementation of the Altman Z-Score and investment risk in both the MVO and robust optimization models.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Altman Z-Score, Himpunan ketidakpastian, Mean Variance Optimization, Robust optimization. ; Altman Z-Score, Mean Variance Optimization, Robust optimization, Uncertainty set.
Subjects:	Q Science > QA Mathematics > QA401 Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Andien Maghfirotus Zahro
Date Deposited:	31 Jul 2025 06:38
Last Modified:	31 Jul 2025 06:38
URI:	http://repository.its.ac.id/id/eprint/124314

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