Do USDT mints pump Bitcoin? 202 on-chain Tether issuances

A popular signal with a simple test

Large USDT mints are widely posted as a bullish signal: new dollars are said to be about to buy Bitcoin. Because Tether issuance happens on public blockchains, the claim can be tested with exact timestamps. We collected every USDT Issue event on Ethereum and Tron and combined mints within 12 hours of each other. From July 2019 to August 2026 there were 202 events of at least US$500 million, totalling about US$240 billion; the median event was US$1 billion.

BTC had usually already risen before the mint

In the 72 hours before these mints, BTC rose an average of 130 basis points, against 48 bp for a typical 72-hour window (t 1.95). That fits the opposite story to the folklore: demand for stablecoins rises when crypto prices are rising, and Tether issues new tokens to meet it.

After the mint, returns looked like any other period. Over the next 24 hours BTC averaged −8 bp against +16 bp for a random hour; over 72 hours +63 bp against +48 bp; over a week +135 bp against +113 bp. None of the differences is statistically meaningful, and half of the 24-hour windows were negative.

Robustness: random hours and daily data

Overlapping events can make a result look stronger than it is, so we also kept only events at least 72 hours apart. The 152 remaining events averaged +31.7 bp over 72 hours. Drawing 152 random hours from the same period 20,000 times produced a higher average 64% of the time.

Many dashboards use a daily stablecoin supply series instead of on-chain events. Using DefiLlama’s daily USDT circulation, the 151 days with a supply increase of at least US$500 million were followed by +92 bp over 72 hours when measured from the start of the labelled day, and +79 bp from its end (t 0.94 and 0.72). Neither clock shows a reliable edge over the 72-hour average of +48 bp.

Year by year

The 72-hour average after a large mint was above the all-hour average in 2021, 2024, 2025 and 2026 and below it in 2019, 2020, 2022 and 2023. In 2024 mints were followed by +178 bp against +75 bp for any hour; in 2022, −234 bp against −69 bp. With 1 to 57 events a year, single years are noisy, and the pooled result is the more informative one.

How the numbers were calculated

Issue events come from the USDT contract logs on Ethereum and from the TronGrid events API for Tron, with block timestamps in UTC. Redemptions are excluded. Returns use Binance BTC/USDT hourly opens, starting at the first full hour after the first mint in an event. The comparison set is every hourly start time from January 2019. t-statistics compare event means with the all-hour mean using the event standard deviation.

Issuance on other blockchains and transfers out of Tether’s treasury are not included; a mint is a supply event, not proof that the tokens were used to buy Bitcoin.

Does Tether minting USDT make Bitcoin go up?

Not on this evidence. Across 202 large mints since 2019, BTC returns over the next one, three and seven days were not meaningfully different from random hours. BTC had typically already risen before the mint, consistent with issuance following demand.

Why do USDT mint alerts look like they work?

Mints cluster in rising markets, so many alerts are followed by further gains simply because the market was already going up. Compared with the average return over the same years, the post-mint returns showed no reliable extra gain.

Limitations

Two blockchains, one price venue and hourly data. Event clustering, the US$500m threshold and the 12-hour merge window are analysis choices. Daily supply series and on-chain logs can differ. No fees, spreads or account-level backtest are included, and the results are not trading advice.

Sources and data access

• Tether: transparency and USDT issuance
• Etherscan: Tether USDT contract
• TronGrid: contract events API
• DefiLlama: USDT circulation
• Binance public data and archive formats

Cited sources document external facts or data formats; they do not endorse our findings. The public snapshot contains the table and methods. Source-file fingerprints are included for recalculated datasets. Full archived raw files are not distributed here; fingerprints identify the files used, rather than independently proving the results.

Aggregate data snapshot (JSON) · Markdown · Methods and limitations

Live prior 30-day hourly baseline — separate from the historical study

Only the current watch list is shown, up to 12 assets. Missing or stale estimates remain unavailable. Venue and quote currency are kept separate; beta needs matching BTC data. Hourly statistics are not minute-move probabilities.

Observation cutoff (UTC): 24/10/2026, 13:44

Related research