Measuring Financial Distress in the Property and Real Estate Sector listed on the Indonesian Stock Exchange
Keywords:
Financial Distress, Altman Z-Score, Springate, Zmijewski, GroverAbstract
This research aims to evaluate the accuracy of four bankruptcy prediction models, namely Altman Z-Score, Springate, Zmijewski, and Grover, in predicting financial difficulties in property and real estate companies listed on the Indonesia Stock Exchange (BEI) during the 2020-2023 period. The data used in this research includes the annual financial reports of the companies selected as samples. The research method involves analyzing quantitative data from financial reports of property and real estate companies on the IDX, using purposive sampling techniques. Descriptive and statistical analysis was carried out to assess the company's condition based on the prediction model used. Research shows that the Grover model has a high level of accuracy in predicting financial distress compared to the other 3 models. The Altman Z-Score model is also considered the most suitable for this sector (Laksita Nirmalasari, 2018; Reza Prabowo & Wibowo, 2015). The research results show that the Grover model has the highest prediction accuracy (73.84%) compared to other models. The Mann Whitney test shows a significant difference between the model prediction results and the company's actual conditions, indicating the importance of choosing the right prediction model to manage the financial risk of property and real estate companies on the IDX.Downloads
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