WLFI’s early plunge and extreme funding rates preceded a $6.9B liquidation cascade across Bitcoin and Ether markets.
Crypto markets saw one of their sharpest shocks of 2025 on Oct. 10, when nearly $7 billion in leveraged positions were wiped out within an hour. Bitcoin and Ether plunged, triggering forced sales across exchanges. Analysis from Amberdata suggests stress began hours earlier in a lesser-known token. Data shows World Liberty Financial Token (WLFI) dropped sharply well before Bitcoin reacted.
Amberdata reviewed trading activity leading up to roughly $6.93 billion in liquidations. Bitcoin fell about 15% during the event, while Ether dropped close to 20%. Smaller tokens declined by as much as 70% in minutes.
WLFI, a DeFi governance token, began sliding more than five hours before broader market prices turned lower. At that time, Bitcoin was trading near $121,000 and exhibited limited signs of strain.
Moreover, researchers identified three unusual patterns in WLFI trading. First, there was a sharp spike in volume. Hourly turnover surged to around $474 million, about 21.7 times normal levels, following public tariff-related political news.
Furthermore, traders were paying extremely high fees to maintain WLFI futures positions. A funding rate of 2.87% every eight hours is unusually steep. Over time, that adds up to very high borrowing costs. Notably, such levels signal crowded trades and strong speculative pressure.
World Liberty Financial Token (WLFI) is a cryptocurrency associated with a lending platform linked to the Trump family. The asset combines digital finance with political branding, an unusual combination in crypto markets.
While most cryptocurrencies react to technological developments or network effects, WLFI responds to political news, policy changes, and regulations. As such, the asset’s price is more sensitive to political events than typical tokens.
The ownership structure of the governance token is also different. While Bitcoin is spread across millions of holders worldwide, WLFI is controlled by a smaller group. Large portions are linked to insiders, including members of the Trump family and political associates. When supply is concentrated, fewer participants can influence price moves.
Meanwhile, political developments may affect these holders more directly. As a result, WLFI can respond more quickly and more sharply to political or regulatory news than broader crypto assets.
Amberdata stressed that the data does not prove insider activity. Instead, the report points to the WLFI market structure as a key factor. The asset’s holder base is more concentrated among politically connected participants.
Cited in the report, the activity was described as “instrument-specific,” meaning trading pressure stayed mostly within WLFI. Activity focused on WLFI, as major coins did not move in unison. If tariff headlines alone had driven the reaction, Bitcoin and other large-cap tokens would likely have declined sooner.
Immediately after the tariff announcement, trading in WLFI increased. That quick reaction suggests some traders were already prepared to make moves. On many crypto platforms, traders borrow money and use tokens such as WLFI as collateral.
When WLFI’s price fell, the value of that collateral dropped. To avoid automatic liquidation, traders had to quickly sell other assets, such as Bitcoin and Ether. Those emergency sales pushed prices down. Falling prices then triggered further forced selling, resulting in billions of dollars in liquidations over a short period.
In addition, the report stated that WLFI’s volatility reached about eight times higher than Bitcoin’s during the crash. This indicates that WLFI responded much more aggressively to market stress.
Researchers believe that fragile and highly leveraged tokens may decline first during shocks. Smaller tokens with concentrated ownership can quickly exert pressure on larger assets.
Amberdata cautioned against treating WLFI as a dependable signal of future downturns. These findings are based on a single event, and more cases would be needed to confirm a consistent pattern.
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