Detecting financial data discrepancy: the case of Korean commercial financial database providers
by Hyun-Jung Nam; Yohan An
International Journal of Business and Data Analytics (IJBDA), Vol. 2, No. 3, 2023

Abstract: Despite the importance of the emerging markets, many previous researches on testing discrepancy of financial data have focused on the US database such as COMPUSTAT, CRSP and value line. Thus, testing discrepancy of financial data among commercial financial data providers has to be expanded to emerging markets due to sustained globalisation. The purpose of this study is to investigate whether there are discrepancies in financial data across commercial financial data providers. Using Altman's (1980) bankruptcy prediction model, we examine how many financial data discrepancies exists between two major commercial financial data providers in Korea. This study finds 1,194 financial data discrepancies out of 20,310 observations, indicating a discrepancy rate of 5.88%. In addition, 5 out of 10 variables have statistically significant discrepancies. These results are much higher than the 2% discrepancy rate in the US database.

Online publication date: Mon, 11-Sep-2023

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