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Deviations from Benford’s law in asset valuations: Market prices vs. expert estimates

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  • Cano-Rodríguez, Manuel

Abstract

This paper examines whether asset valuations based on human judgment deviate more from Benford’s Law (BL) than those based on market prices. Using over 120 million observations from SEC N-PORT filings, this paper uses the fair value hierarchy (FV1, FV2, FV3) to examine how different degrees of human input in asset valuation affect conformity with BL. Aggregate analysis shows that, although level 1 fair value valuations, based on market prices, conform more closely to Benford’s Law, deviations for expert-driven estimates—levels 2 and 3 fair value estimates—are remarkably modest. In the asset-category analysis, some FV1 values deviate more than their FV2 or FV3 counterparts. These findings caution against assuming that market prices always conform to BL or that expert-driven estimates necessarily diverge.

Suggested Citation

  • Cano-Rodríguez, Manuel, 2025. "Deviations from Benford’s law in asset valuations: Market prices vs. expert estimates," Finance Research Letters, Elsevier, vol. 86(PB).
  • Handle: RePEc:eee:finlet:v:86:y:2025:i:pb:s1544612325017465
    DOI: 10.1016/j.frl.2025.108492
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    1. Dan Amiram & Zahn Bozanic & Ethan Rouen, 2015. "Erratum to: Financial statement errors: evidence from the distributional properties of financial statement numbers," Review of Accounting Studies, Springer, vol. 20(4), pages 1594-1595, December.
    2. Roy Cerqueti & Claudio Lupi, 2021. "Some New Tests of Conformity with Benford’s Law," Stats, MDPI, vol. 4(3), pages 1-17, September.
    3. Andreas Diekmann, 2007. "Not the First Digit! Using Benford's Law to Detect Fraudulent Scientif ic Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(3), pages 321-329.
    4. Deckert, Joseph & Myagkov, Mikhail & Ordeshook, Peter C., 2011. "Benford's Law and the Detection of Election Fraud," Political Analysis, Cambridge University Press, vol. 19(3), pages 245-268, July.
    5. Lin William Cong & Xi Li & Ke Tang & Yang Yang, 2023. "Crypto Wash Trading," Management Science, INFORMS, vol. 69(11), pages 6427-6454, November.
    6. Roy Cerqueti & Claudio Lupi, 2023. "Severe testing of Benford’s law," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 677-694, June.
    7. Micha Kaiser, 2019. "Benford'S Law As An Indicator Of Survey Reliability—Can We Trust Our Data?," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1602-1618, December.
    8. Nermina Mumic & Peter Filzmoser, 2021. "A multivariate test for detecting fraud based on Benford’s law, with application to music streaming data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 819-840, September.
    9. Dan Amiram & Evgeny Lyandres & Daniel Rabetti, 2025. "Trading Volume Manipulation and Competition Among Centralized Crypto Exchanges," Management Science, INFORMS, vol. 71(10), pages 8604-8622, October.
    10. Tomasz Michalski & Gilles Stoltz, 2013. "Do Countries Falsify Economic Data Strategically? Some Evidence That They Might," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 591-616, May.
    11. Eutsler, Jared & Kathleen Harris, M. & Tyler Williams, L. & Cornejo, Omar E., 2023. "Accounting for partisanship and politicization: Employing Benford's Law to examine misreporting of COVID-19 infection cases and deaths in the United States," Accounting, Organizations and Society, Elsevier, vol. 108(C).
    12. Horton, Joanne & Krishna Kumar, Dhanya & Wood, Anthony, 2020. "Detecting academic fraud using Benford law: The case of Professor James Hunton," Research Policy, Elsevier, vol. 49(8).
    13. Wolfgang Kössler & Hans-J. Lenz & Xing D. Wang, 2024. "Some new invariant sum tests and MAD tests for the assessment of Benford’s law," Computational Statistics, Springer, vol. 39(7), pages 3779-3800, December.
    14. Tomasz Kamil Michalski & Guillaume Stoltz, 2010. "Do countries falsify economic date strategically? Some evidence that they do," Working Papers hal-00540794, HAL.
    15. Arash Aloosh & Jiasun Li, 2024. "Direct Evidence of Bitcoin Wash Trading," Management Science, INFORMS, vol. 70(12), pages 8875-8921, December.
    16. Christoph Watrin & Ralf Struffert & Robert Ullmann, 2008. "Benford’s Law: an instrument for selecting tax audit targets?," Review of Managerial Science, Springer, vol. 2(3), pages 219-237, November.
    17. Ausloos, Marcel & Cerqueti, Roy & Mir, Tariq A., 2017. "Data science for assessing possible tax income manipulation: The case of Italy," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 238-256.
    18. Lucio Barabesi & Andrea Cerioli & Marco Marzio, 2023. "Statistical models and the Benford hypothesis: a unified framework," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(4), pages 1479-1507, December.
    19. Lucio Barabesi & Andrea Cerasa & Andrea Cerioli & Domenico Perrotta, 2018. "Goodness-of-Fit Testing for the Newcomb-Benford Law With Application to the Detection of Customs Fraud," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 346-358, April.
    20. Dan Amiram & Zahn Bozanic & Ethan Rouen, 2015. "Financial statement errors: evidence from the distributional properties of financial statement numbers," Review of Accounting Studies, Springer, vol. 20(4), pages 1540-1593, December.
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