Determinants of cryptocurrency pricing

This study aims to examine how digital assets in the cryptocurrency market respond to external economic and financial shocks within a functional classification framework. Based on the five-category classification proposed by Kraken exchange (payment, financial, infrastructure, utility, and media tokens), the pricing dynamics of each token class are analyzed. The empirical analysis relies on weekly data from the 2023–2025 period. Class-specific indices are used as dependent variables, while S&P 500, NASDAQ, gold and oil prices, and Google Trends data serve as independent variables. Stationarity of the time series is tested using the Augmented Dickey-Fuller (ADF) test. VAR models are estimated to assess Granger causality, and impulse response functions are employed to evaluate temporal effects of shocks. To test for cross-class sensitivity differences, a SUR model and Wald tests are applied. Findings reveal that although token classes show functional separation, their pricing behavior exhibits strong convergence in response to systemic shocks, reflecting the market's speculative and structurally integrated nature. The study empirically evaluates the limits and potentials of functional classifications for investment strategies, portfolio diversification, and regulatory design.