Granger Causality: Does USDT Lead or Lag USDC?
Granger causality tests whether knowing yesterday's USDT market cap change helps predict today's USDC change — beyond what USDC's own history already tells us. If yes, USDT Granger-causes USDC: it is a leading indicator of USDC issuance and redemption cycles. This is not classical causation — it is predictive precedence in the time-series sense (Granger, 1969). For the stablecoin market, the question is whether Tether's issuance dynamics lead Circle's, or vice versa — revealing which issuer responds to market demand first, and which follows. The test is computed on daily market cap % changes, which for dollar-pegged stablecoins are equivalent to net minting and redemption flow signals. As of Apr 2026, over 366 daily snapshots from Apr 2025: Neither (p > 0.05).
Rolling Granger F-Statistic — USDT ↔ USDC
Rolling Granger F-statistic for both directions over the selected window. Amber dashes mark F = 3.84 (p < 0.05); coral dashes mark F = 6.63 (p < 0.01). Values above a threshold reject the null that the leading series adds no predictive value. Sustained crossing of the 3.84 line signals an emerging structural lead-lag relationship.
Current F-Statistics — Both Directions
F-statistics for both directions at the selected window. Bars are coloured when above F = 3.84 (p < 0.05). A higher bar in one direction indicates that direction as the primary predictor. Amber dashes mark the significance threshold.
Window Sensitivity — 30D / 60D / 90D
F-statistics across all three rolling windows. Consistency across windows signals a robust structural relationship. Divergence suggests the lead-lag may be regime-specific rather than persistent.
The F-statistic exceeds the 99% significance threshold. The leading series provides highly significant predictive information about the following series. This is a robust structural lead-lag relationship. For policymakers: the leading issuer's operations are a reliable early warning signal for the follower's flows.
For enterprise: Build treasury strategy around the leading issuer's minting signals — they are a confirmed leading indicator. For policymakers: The leading issuer's capital flows are a systemic early indicator worth monitoring.
F-statistic is above 95% threshold but below 99%. The relationship is statistically significant but may be driven by a specific regime or short period. If this coincides with a market expansion or stress episode, it may reflect a temporary information spillover rather than a structural lead.
For enterprise: Treat as confirming — not standalone — signal. Monitor across subsequent windows. For policymakers: Worth tracking; may solidify into a robust lead over time.
The series does not provide statistically significant predictive information about the other. USDT and USDC are likely responding to the same contemporaneous signals — macro liquidity conditions, crypto market flows — rather than to each other's lagged signals. This is the baseline for mature, liquid markets where information is quickly reflected across issuers.
For enterprise: No exploitable lead-lag at this window — both issuers react simultaneously to demand. For policymakers: Market is informationally efficient across the two primary issuers.
Test: Granger causality F-test (Granger, 1969) with 1 lag. Tests whether lagged values of X significantly improve predictions of Y beyond Y's own history. Implemented by comparing a restricted model (AR(1) in Y) to an unrestricted model (AR(1) in Y + lagged X). F-statistic: F = ((RSS_r − RSS_u) / 1) / (RSS_u / (n − 3)), where q = 1 restriction, k = 3 parameters (intercept + Y_lag + X_lag). The Frisch–Waugh–Lovell theorem is used for numerical stability: the X coefficient is estimated from residuals after partialling out Y_lag from both Y and X.
Data: Daily market cap % changes (ΔMcap/Mcap) for USDT and USDC from CoinGecko daily snapshots. Market cap % changes are equivalent to net minting/redemption flow signals for dollar-pegged stablecoins.
Thresholds: F = 3.84 (p < 0.05 for F(1, ∞)) and F = 6.63 (p < 0.01 for F(1, ∞)). Exact p-values require numerical CDF evaluation; these thresholds are used as practical decision boundaries. For short windows (n < 50), treat results with caution — finite-sample critical values are slightly higher.
Important caveat: Granger causality is not classical causation. "USDT Granger-causes USDC" means USDT's past values help predict USDC's future values — not that Tether causes Circle to issue stablecoins. It reveals information spillovers and issuance timing dynamics.
Data source: CoinGecko API (daily snapshots). Update frequency: Daily at ~15:30 UTC. Coverage: Apr 2025 – present (366 snapshots). Computation runs entirely in the browser.