SUI +103.11% in 24 Hours as Market Volatility Intensifies

On SEP 3 2025, SUI surged by 103.11% within 24 hours to reach $3.3349, marking a significant turnaround in its price trajectory. Over the last seven days, the asset climbed 209.62%, and in the past month, it increased by 312.67%. While the annual performance remains negative at -1871.44%, the recent rally has sparked renewed interest in SUI’s market behavior and technical outlook.

SUI’s sharp rebound appears to be driven by a consolidation of on-chain activity and a favorable shift in its technical indicators. The price has broken above a long-standing resistance zone, suggesting a potential shift from a bearish to a bullish sentiment among traders. The 20-day moving average has crossed above the 50-day line, reinforcing the notion of a short-term reversal. Traders have noted increased buying pressure in the $2.50 to $3.00 range, which had previously acted as a key support level.

The 14-day RSI has moved from oversold territory into neutral ground, indicating a stabilization in momentum. Analysts project that SUI could retest the $3.50 level in the near term, with the potential to extend gains to $4.00 if bullish volume confirms the breakout. A failure to maintain the $3.00 level would likely signal a return to consolidation.

Backtest Hypothesis

To assess the validity of the recent bullish movement, a backtesting strategy has been proposed, focusing on a set of technical indicators aligned with the observed price action. The strategy employs a combination of the 20-day and 50-day moving averages to identify potential trend changes, alongside the RSI to gauge momentum shifts. A long position is triggered when the 20-day moving average crosses above the 50-day line and the RSI is above 40, indicating an emerging uptrend and sufficient momentum to sustain it. Stop-loss levels are placed below the most recent swing low, while take-profit targets are set at the nearest resistance level and beyond. This strategy aims to capture the early phases of a breakout and is designed to be applied in real-time across various timeframes.