Background: As financial professionals including policy-makers tend to base decisions on research performed using large machine-readable financial databases, the accuracy of the financial data provided by database companies has a direct impact on the quality of their decisions. Objectives: The objective of this study was to examine data errors in the DataGuide and KisValue databases which are both primary sources of stock prices and return data for Korea Exchange securities in Korea. This article also discussed the methodological implications of erroneous data on monthly stock returns in empirical studies on Korean financial markets. Methods: A cross-checking technique was used in this study. Results: The results suggest that there are material discrepancies between the DataGuide and KisValue databases in monthly stock returns, most of which are attributable to the mishandling of split events and of missing values. The results also indicate that DataGuide provides a more reliable service than KisValue in terms of monthly stock returns. Conclusion: The results show that extreme monthly returns resulting from serious data errors in the DataGuide and KisValue databases may be enough to sharply change the properties of monthly stock return distributions and to over- or underestimate long-term abnormal stock returns.

中文翻译：

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金融信息数据库中的数据错误分析：韩国金融市场的新证据

背景：由于包括决策者在内的金融专业人士倾向于根据使用大型机读金融数据库进行的研究做出决策，因此数据库公司提供的财务数据的准确性直接影响其决策质量。目标：这项研究的目的是检查DataGuide和KisValue数据库中的数据错误，它们既是股价的主要来源，又是韩国Korea Exchange证券的回报数据。本文还讨论了韩国金融市场的实证研究中错误数据对每月股票收益率的方法学影响。方法：本研究使用交叉检查技术。结果：结果表明，每月股票收益中DataGuide和KisValue数据库之间存在重大差异，其中大多数归因于拆分事件的处理不当和缺少值。结果还表明，就每月的股票回报而言，DataGuide提供的服务比KisValue更可靠。结论：结果表明，由DataGuide和KisValue数据库中的严重数据错误导致的极高月度回报可能足以急剧改变月度股票回报率分布的特性，并高估或低估了长期异常股票回报率。