MANTA -110.29% in 24 Hours Amid Sharp Volatility

MANTA plummeted by 110.29% in 24 hours as of AUG 29 2025, closing at $0.2102, marking one of the most severe single-day declines in recent record. The asset’s performance reflects extreme short-term instability, exacerbated by ongoing speculative trading and liquidity constraints. Despite a 346.15% surge over the past month, the 7-day decline of 515.65% highlights the highly volatile nature of the asset class.

The drop follows a broader trend of heightened risk aversion in crypto markets, with investors retreating from high-beta assets following a series of failed price recoveries. Analysts project that further downward pressure could persist unless a sustained buyer’s interest emerges. While long-term holders remain optimistic about the underlying use cases of MANTA, the immediate technical outlook remains bearish.

Technical analysis points to a breakdown below key support levels, with the 20-day and 50-day exponential moving averages now acting as resistance rather than support. This has triggered sell-side momentum, particularly in overleveraged positions, leading to cascading liquidations. The RSI has fallen below 30, signaling potential oversold conditions, though without a corresponding bounce in price, the indicator remains in bearish territory.

MANTA’s 1-year decline of 7323.38% underscores the long-term erosion in value, pointing to structural concerns about adoption, utility, and governance. Market participants are closely monitoring on-chain metrics for signs of stabilization, including reduced short-term selling pressure and increased inflows into non-custodial wallets. However, the absence of a clear catalyst for recovery has left the asset vulnerable to further downside risk.

Backtest Hypothesis

To better understand potential strategies in navigating MANTA’s volatility, a backtest framework could be constructed based on the asset’s behavior. A backtesting strategy would need to define the following parameters: the universe of assets (single ticker or a broader index), the entry rule (e.g., a 10% decline on a close-to-close basis), the holding period (fixed duration or based on profit/loss thresholds), and position sizing. Once these details are established, the effectiveness of a given strategy in capturing or avoiding losses can be evaluated using historical data from 2022-01-01 to the present. This would help in identifying whether a systematic approach could have mitigated exposure during sharp drawdowns like the one observed on AUG 29.