Valuation of Cryptocurrencies: Exploring Network Value to Transactions Ratio and Sentiment Analysis Approaches

Abstract

Cryptocurrency valuation remains a significant challenge for investors and analysts due to the sector's volatility, evolving regulatory landscape and dependence on technology and market psychology. This paper reviews two prominent approaches for cryptocurrency valuation—Network Value to Transactions (NVT) Ratio and Sentiment Analysis. It outlines their methodologies, applications and limitations. The NVT Ratio is compared to the price-to-earnings ratio in equity markets and evaluates a cryptocurrency’s market capitalization relative to network transaction volumes. Sentiment Analysis evaluates public mood and opinion by mining social media, news and community forums to forecast price movements. Supporting literature is explored, including innovative concepts like Data Shapley value and advanced prediction models using deep learning. Using Bitcoin and Ethereum as examples, the study demonstrates step-by-step calculations and interpretations, showing how each approach can offer insights into market conditions. The paper concludes that combining quantitative and qualitative models can provide more balanced and reliable cryptocurrency valuations for informed decision-making.