Are There Behavioral Types of Stablecoins?

Stablecoins are commonly classified according to their issuers’ stated design, such as fiatbacked, crypto-backed, or algorithmic. This note asks whether they also sort into discrete behavioral types. We examine 111 stablecoins that survived and were adequately observed through the first 180 days after first sustaining $1 million in the issuance record. Six behavioral measures are calculated using observations from days 0 to 179 only, so subsequent outcomes do not enter the measurement. Three rotated principal components explain 95% of the variance and capture local peg stability, supply trajectory, and supply volatility. We test for discrete groups using an explicitly stated decision rule calibrated on simulated samples of the same size, including 2,000 draws from a Gaussian-copula continuum preserving the empirical marginals and planted three-group mixtures of known separation. The observed data do not satisfy the rule: cluster separation remains within the continuum reference range at every partition size, the overlap-penalized mixture criterion selects one component, and no partition’s bootstrap reproducibility exceeds its continuum reference. The rule’s false-positive rate is 0.1%; it detects planted groups separated by four standard deviations of the leading component in 99% of simulations and by three in 15%. Declared backing category explains 4% of score variance in the fiat-backed versus cryptobacked comparison (permutation p = 0.006). Fiat-backed coins are more stable around local par, with less drawdown and stronger supply growth. Within this population, coins are better described by their position on continuous coordinates than by membership in behavioral types; groups separated by three standard deviations or less would not usually be detected.