The website Portfolio Management Research has published an article in The Journal of Alternative Investments by researchers from the Digital Finance Department Andrey Zubarev, Vera Larionova and Kirill Shilov, a Researcher at the Institute of Applied Economic Studies (IAES) of the Russian Presidential Academy of National Economy and Public Administration (RANEPA)—Explaining DeFi Token Returns: Do Protocol Metrics and Broader Crypto Trends Matter?
The paper examines the factors influencing the returns of governance tokens in decentralized finance (DeFi) protocols, using COMP, AAVE, and CRV as examples for the period from January 2021 to March 2025. Unlike previous studies, which typically consider a limited set of explanatory factors, this paper uses a broader list of internal protocol metrics. The analysis includes protocol activity metrics, financial indicators, treasury reserves, and various market metrics of the tokens themselves, including trading volumes, the number of holders, and market multiples. Linear regression is used to assess the relationship between weekly token returns, internal protocol characteristics, and Ether returns as a proxy for cryptocurrency market dynamics. The study’s findings indicate that DeFi token returns are determined not only by overall market dynamics but also by the characteristics of the protocols themselves. At the same time, the relative importance of these factors varies depending on the type of protocol: for lending protocols, the relationship with Ether plays a key role, whereas for decentralized exchanges, the influence of individual internal metrics, such as Total Value Locked (TVL) and net reserves, is more pronounced. This work contributes to the literature on decentralized finance by offering a comprehensive analysis of the relationship between governance token returns and several groups of protocol metrics, highlighting differences in the drivers of various types of DeFi protocols, and challenging the notion that DeFi tokens merely track Ether’s dynamics. The findings highlight the need to account for specific characteristics when constructing DeFi asset valuation models.