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Fraud characteristics and their effects on shareholder wealth

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Abstract

This study examines characteristics of fraud cases and their effects on shareholder wealth in Germany. Using a sample of 126 fraud cases of listed German firms that became public between 1998 and 2014, we provide evidence that shareholder value decreases significantly in the days surrounding the revelation of a fraud case. Our analysis shows that shareholder wealth losses are remarkable, with a mean (median) loss of 80.78 million euros (47.03 million euros). Further, we find that the characteristics of fraud cases affect the financial consequences to investors. Our results indicate that shareholder wealth decreases more if at least one board member resigns due to the fraud case, but less if firms identify and reject accountable employees. Moreover, shareholder wealth decreases less if firms are willing to cooperate with legal authorities. Exploratory analysis suggests that reputational penalties are considerable for German firms. Our study contributes not only to accounting and corporate governance theory but also to practice in a number of ways. Our results reveal areas that are particularly important for regulators and where effective internal control systems are particularly beneficial. Further, our study identifies critical aspects that firms should consider in their communication with investors when fraud occurs.

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Notes

  1. Sutherland (1945) seminal work uses the term white-collar crime. Other researchers use the term misconduct to denote all types of illegal business behavior (e.g., Murphy et al. 2009; Tibbs et al. 2011). Since the term fraud has become more common in recent years, we refer to white-collar crime with the term fraud throughout the paper.

  2. Karpoff and Lott (1993) also differentiate between four types of fraud. However, the authors do not analyze whether different types of fraud lead to different market reactions.

  3. In line with Alexander (1999), the concept of reputational penalty excludes payments that offending firms have to make to restore their level of reputation prior to the discovery.

  4. In Germany, stock corporations (Aktiengesellschaft) must employ the dualism of a management board (Vorstand) and a separate supervisory board (Aufsichtsrat), which is often called a two-tier system.

  5. We excluded the newspaper Financial Times Deutschland from our analysis because it ceased publication in December 2012 and its press archive is no longer available.

  6. Regarding the coverage of the fraud cases in the media, 13.5 % of the fraud cases were covered in only one of the four newspapers, 23.0 % in two newspapers, and 42.1 % in three newspapers. 21.4 % of the fraud cases were reported in all four newspapers. However, the online archive of Börsenzeitung is only available since 2001. Therefore, the reported percentages are likely to underestimate the coverage in the media slightly.

  7. A short event window is important for measuring reliable abnormal rates of return (Brown and Warner 1985). For instance, McWilliams and Siegel (1997) criticize many event studies for using event windows that are too long to systematically exclude other events.

  8. Using this model results in smaller variances of abnormal returns compared to raw returns, yielding more powerful statistical tests (Beaver 1981).

  9. To assess the induced collinearity, we also computed variance inflation factors, whose maximum was 4.10, well below the critical level of 10.

  10. There are 125 observations for the Fama–French model because Fama–French factors were only available until the end of June 2014, while one fraud case was revealed in September 2014.

  11. Though we have directed hypotheses, we took the conservative approach and refrained from using one-tailed t tests.

  12. We exclude five fraud cases that relate to more than one fraud type. Therefore, the subsample sizes do not add up to our total sample of 126 fraud cases.

  13. A more detailed comparison with prior research fails because prior research generally uses less granular categories.

  14. We also deploy an alternative proxy for media coverage, namely, the number of newspapers that cover a respective fraud case. The results are not affected.

  15. The cases are selected based on their relevance to investors according to the capital market reactions.

  16. Values for non-euro data are converted into euros using the event day.

  17. We acknowledge that in the Hess fraud case, the result can also be interpreted as a valuation correction.

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  1. University of Münster, Universitätsstr. 14-16, 48143, Münster, Germany

    Corinna Ewelt-Knauer

  2. University of Bayreuth, Universitätsstr. 30, 95447, Bayreuth, Germany

    Thorsten Knauer

  3. Berlin Institute of Technology, Straße des 17. Juni 135, 10623, Berlin, Germany

    Maik Lachmann

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Ewelt-Knauer, C., Knauer, T. & Lachmann, M. Fraud characteristics and their effects on shareholder wealth. J Bus Econ 85, 1011–1047 (2015). https://doi.org/10.1007/s11573-015-0773-5

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