DETECTION OF FINANCIAL DISTRESS IN TECHNOLOGY COMPANIES LISTED ON THE INDONESIAN STOCK EXCHANGE

Abstract

The purpose of this study is to determine and analyse the sensitivity of the results of financial distress analysis using the Ohlson and Grover models to predict financial distress in technology companies listed on the IDX for the 2020-2022 period. The study employs quantitative data extracted from the financial statements of technology companies listed on the Indonesia Stock Exchange (IDX) from 2020 to 2022. Utilizing the Ohlson and Grover models, the research aims to detect financial distress within these technology firms and determine the sensitivity level of the two models. This descriptive research design relies on secondary data sources, emphasizing the objectivity and popularity inherent in data-driven analyses. The research results of financial distress detection analysis, Ohlson model detects 10 distress zones and 8 safe zones, while Grover model detects 5 distress zones, 1 gray zone and 12 safe zones. From this analysis, the Grover model shows a higher level of sensitivity in recognizing financial distress with 12 samples consistent with the results of the Grover model analysis.