Active tokens and crypto-asset valuation

Abstract

This research investigates token dormancy as a fundamental metric for evaluating cryptocurrency assets and presents a methodology for its measurement. The valuation method involves 4 distinct parameters and utilizes a 3.5-year daily dataset for the “Chainlink” token. The results are used in optimized ARIMA-GARCH models to analyze the first differences between the variables; the out-of-sample forecasts were assessed with performance metrics. Furthermore, this study introduces a novel fundamental value derived from these approaches, the basis for generating selling signals in a backtested trading strategy. The trading strategy results are compared to a benchmark buy-and-hold strategy and a non-selling dollar-cost-averaging strategy for evaluation. Employing the dollar-cost averaging approach for purchase frequency and utilizing the “isolation forest” technique for identifying selling signals within the trading strategy yielded positive results.