In May 2026, the IVSC‘s Valuation Risk Working Group published a Perspectives Paper “Managing and Communicating Value Uncertainty” that deserves the attention of every valuer working internationally. Its core message is simple but easily forgotten in daily practice – value uncertainty is not a sign that a valuation has failed. It is an inherent feature of estimating the worth of complex assets in complex markets, and it is analytically distinct from valuation risk, which reflects genuine errors or process failures.
This same push toward disciplined, defensible methodology is exactly what motivates EACVA’s newest initiative: the CDAV – Certified Digital Asset Valuator. Digital assets are, almost by definition, an asset class where value uncertainty is unusually pronounced – thin markets, volatile on-chain data, and evolving regulation all complicate the picture. Digital assets have long outpaced the profession‘s ability to value them consistently. Institutional crypto exposure continues to grow, DeFi protocols now sit on hundreds of billions in locked value, and regulators from MiCA to IFRS are asking hard questions about fair value, stablecoin reserves, and NAV calculations for token portfolios – yet a standardised, defensible valuation methodology has largely been missing. The CDAV was developed to close that gap: a practice-oriented curriculum that bridges established valuation principles with blockchain infrastructure, tokenomics, and DeFi mechanics, culminating in a real-world case study rather than a purely theoretical exam. This issue of EBVM asks a question that runs beneath almost every valuation engagement, however different the four contributions may appear on the surface: how much can we trust the numbers we produce, and how well can we explain where that trust comes from?
Karagiannidis opens the issue with a guest essay written from the vantage point of the Greek mid-market, where multiples-based pricing still dominates deal practice. Ernst/Kamarás then turn to a methodological frontier: simulation-based corporate planning and valuation. Building on a case study, they present a structured process in which Monte Carlo simulation is used not merely to stress-test a plan, but to derive the cost of equity itself from the company‘s own risk position – explicitly incorporating insolvency risk along the way. Pattikawa’s contribution addresses the cost of equity from a different angle entirely – not its statistical construction, but its role as a communication device. Contrasting covariance-based models such as CAPM with cash-flow-implied approaches derived from the relationship between FCFE, growth, and price. Finally, Knoll/Lorenz/Manthey take a critical look at debt beta, a concept that has gained increasing traction in valuation practice over the past two decades. Taken together, these four articles circle back to a common theme: valuation is only as credible as the transparency of the assumptions behind it.
We hope these contributions prompt discussion within your own practice, and, as always, we look forward to your feedback.
