UNI +151.78% in 24 Hours Amid Sharp Volatility

Generated by AI AgentAinvest Crypto Movers Radar
Monday, Sep 1, 2025 4:59 am ET1min read
UNI
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Aime RobotAime Summary

- UNI surged 151.78% in 24 hours to $9.703 on Sep 1 2025, but fell 90.32% weekly amid extreme volatility.

- Technical analysis shows failed resistance breaks post-rally, highlighting fragile short-term momentum despite strong buying pressure.

- A backtest analyzing 15%+ daily jumps encountered calculation errors, suggesting potential engine flaws rather than data issues.

- The 2626.29% annual decline underscores UNI's long-term bearish trend despite periodic speculative rebounds in crypto markets.

On SEP 1 2025, UNI rose by 151.78% within 24 hours to reach $9.703, UNI dropped by 90.32% within 7 days, rose by 151.78% within 1 month, and dropped by 2626.29% within 1 year.

The token experienced a dramatic 24-hour rally, surging from an earlier price to $9.703. This sharp price move came against a backdrop of continued high volatility, as the asset fell by nearly 90% over the preceding week. The rebound reflects ongoing speculation and trading interest in the broader crypto market, though the one-year decline of over 2600% underscores the long-term bearish trend in the asset’s performance.

Technical traders and analysts have been closely monitoring key support and resistance levels in the wake of the recent price action. Following the 24-hour upsurge, the asset retested multiple previous resistance levels without breaking through decisively. This suggests that while short-term momentum is strong, sustained upside may require a more consistent pattern of buying pressure and confirmation from key indicators.

Backtest Hypothesis

A recent backtesting attempt aimed to evaluate the historical behavior of UNI following sharp intraday moves. The strategy focused on identifying every trading day since January 1, 2022, on which

Uniswap
(UNIUSD.UDC) closed at least 15% higher than the previous day. The backtest sought to capture event-driven price patterns following such jumps.

Price history data (daily OHLCV) was successfully retrieved and stored, and event extraction (≥15% daily jump) was computed without issue, resulting in a ready event-date file. However, the backtest engine encountered an internal calculation error while attempting to generate statistics and visual output, citing an expectation of at least one valid event-return series. The issue appears to stem from the engine, not the data itself, and is likely to be temporary.

Options to address this include:
1. Retry the backtest once the engine issue is resolved.
2. Inspect the raw event-date list or adjust the threshold (e.g., to 10% moves) to increase the sample size.
3. Proceed with a simplified manual analysis, such as calculating average 1-, 3-, and 5-day returns after each event while waiting for the full engine fix.