River (RIVER) fluctuated by 43.0% in 24 hours: Token unlocking selling pressure triggers sharp volatility
Bitget Pulse2026/03/27 16:02Volatility Brief
In the past 24 hours, RIVER price fell from a high of $18.40 to a low of $12.8693. The current price is $13.178, with a price fluctuation range of 43.0%. The 24-hour trading volume is approximately $41.57 million to $52.04 million, up over 70% from the previous day, indicating a significant increase in market activity.
Analysis of the Causes of the Fluctuation
• Token unlock selling pressure: The unlock event triggered more than 20% panic selling, with prices rapidly breaking through support levels followed by a liquidity sweep.
• Profit-taking and correction: Despite nearly a 90% increase in the past month, RIVER still plunged 23%-30% within 24 hours, wiping out about $96 million to $124 million in market capitalization, mainly as a normal correction after the previous pump.
Market Perspective and Outlook
The mainstream market sentiment is cautiously optimistic. The community describes this move as a “whipsaw” fluctuation; a brief squeeze occurred after the sell-off, MACD still shows bullish signals, and top holders did not significantly reduce their positions. Analysts point out that demand signs persist but warn of the risks of leveraged trading. Future market developments should pay attention to structural support levels.
Note: This analysis is automatically generated by AI based on public data and on-chain monitoring and is for informational purposes only.Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
You may also like

Japanese Yen gathers strength as BoJ hike bets ramp up
The True Significance of GPT-6 Astra: Bringing the "AI Narrative" Back from "Demand Disputes" to "Physical Limitations"
Morgan Stanley believes that the release of GPT-6 Astra shifts the AI narrative focus from “is there excess demand” to “can physical supply keep up.” The leap in capabilities brought by Astra will trigger more AI revenue-generating scenarios. However, the real hard constraints limiting the release of AI dividends are the shortage of ABF substrates, manufacturing bottlenecks in HBM4E, and a 38-gigawatt power gap. Morgan Stanley’s prioritization is as follows: AI computing power takes top priority, followed by networks; memory is selectively allocated, and analog chips act as early-cycle hedges.
