The article addresses the scientific problem of forming an efficient approach to assessing the market value of business projects in the rapidly evolving area of decentralized finance (DeFi) within the digital economy. The article analyzes the limitations of applying traditional financial evaluation methods, specifically discounted cash flow (DCF) models and economic value added (EVA), which lose their relevance in the DeFi context due to the instability of cash flows, absence of centralized reporting, and the specific profitability structure of tokenized assets. In order to overcome the mentioned limitations in the study, a new multifactor model has been proposed, which combines classical financial indicators with key tokenomic metrics: total value locked (TVL), the utility function of the token in governance, liquidity mining incentives, as well as the distribution of tokens over time (vesting schedules). An empirical validation of the model’s efficiency was conducted through the construction of a multiple linear regression based on data from 20 leading DeFi projects for the years 2023–2024. The results obtained demonstrated a high statistical significance of the included tokenomic variables (p < 0.01) and a high explanatory power of the model (R? = 0.92), confirming its efficiency for predicting the market capitalization of digital assets. It is demonstrated that tokenomic characteristics have a decisive impact on the value of DeFi projects, while traditional indicators (DCF, EVA) are secondary or insignificant due to the changing nature of value in the Web3 economy. The proposed model enables the development of a sound methodology for the strategic analysis of investment attractiveness of decentralized platforms, particularly from the perspective of DAO organizations, venture funds, and analytical agencies.
Ivakhno et al. (Wed,) studied this question.