The effect of adopting tokenized assets on accounting discretion in fair value measurement under IFRS 9 and IFRS 13

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Type of the article: Research Article

 

Blockchain technology poses significant challenges for asset classification, valuation hierarchy, and disclosure under IFRS 9 and IFRS 13. Given that observable market prices are often unavailable, entities rely on Level 3 internal valuation models, which reduces comparability between companies. This study examines how the adoption of tokenized assets affects accounting discretion in fair value measurement under IFRS 9 and IFRS 13. The analysis uses panel data from 2,735 Peruvian companies (687 financial, 724 industrial, 658 commercial, and 666 service companies) selected from the database of the Superintendency of Securities Market using systematic exclusion criteria based on the explicit adoption of IFRS 9/13 and complete financial statements for 2020-2024. An ordinary least squares regression with robust standard errors and fixed effects was applied to test three hypotheses. The results show that tokenization significantly increases accounting discretion in fair value measurement (β = 0.284, p < 0.001, R² = 0.694), contradicting expectations that blockchain reduces discretion. Fair value measurement using the IFRS 13 Level 3 hierarchy also increases discretion (β = 0.219, p < 0.001), while greater disclosure is associated with greater discretion (β = 0.173, p < 0.01). Conversely, larger companies (β = −0.104, p < 0.001) and Big Four audits (β = −0.142, p < 0.01) are associated with lower discretion. All three hypotheses were confirmed across all sectors, and sensitivity analyses support their robustness. The results underscore the need for stronger regulatory guidance and greater oversight of audits in digital asset accounting under IFRS 9 and IFRS 13.

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    • Table 1. Sample selection and refinement (N = 2,735)
    • Table 2. Operational definition of variables
    • Table 3. Descriptive statistics (N = 2,735)
    • Table 4. Pearson correlation matrix (N = 2,735)
    • Table 5. Effect of tokenization on accounting discretion
    • Table 6. Robustness analysis, coefficients by economic sector
    • Conceptualization
      Miluska Odely Rodriguez-Saavedra, Antonio Victor Morales Gonzales
    • Investigation
      Miluska Odely Rodriguez-Saavedra, Ivan Cuentas Galindo, Luis Miguel Campos Ascuña, Antonio Victor Morales Gonzales
    • Supervision
      Miluska Odely Rodriguez-Saavedra
    • Validation
      Miluska Odely Rodriguez-Saavedra, Ivan Cuentas Galindo, Luis Miguel Campos Ascuña, Adolfo Erick Donayre Sarolli, Ruben Washington Arguedas Catasi
    • Writing – original draft
      Miluska Odely Rodriguez-Saavedra, Adolfo Erick Donayre Sarolli
    • Data curation
      Ivan Cuentas Galindo, Antonio Victor Morales Gonzales, Ruben Washington Arguedas Catasi
    • Methodology
      Ivan Cuentas Galindo, Adolfo Erick Donayre Sarolli
    • Software
      Ivan Cuentas Galindo, Luis Miguel Campos Ascuña, Antonio Victor Morales Gonzales, Ruben Washington Arguedas Catasi
    • Writing – review & editing
      Ivan Cuentas Galindo, Ruben Washington Arguedas Catasi
    • Formal Analysis
      Luis Miguel Campos Ascuña, Ruben Washington Arguedas Catasi
    • Project administration
      Luis Miguel Campos Ascuña
    • Funding acquisition
      Antonio Victor Morales Gonzales, Ruben Washington Arguedas Catasi
    • Resources
      Antonio Victor Morales Gonzales, Ruben Washington Arguedas Catasi
    • Visualization
      Adolfo Erick Donayre Sarolli