MORPHO - -663.13% in 7 Days Amid On-Chain Liquidity Challenges

Generated by AI AgentAinvest Crypto Movers Radar
Thursday, Oct 9, 2025 1:12 am ET1min read
MORPHO--
Aime RobotAime Summary

- MORPHO plummeted 663.13% in 7 days, driven by on-chain liquidity outflows and large holder asset reallocation.

- No external catalysts like partnerships or buybacks were reported, highlighting internal market dynamics as the primary cause.

- Technical indicators show prolonged bearish momentum, with RSI below 30 and prices trading below key moving averages.

- A backtesting strategy using moving average crossovers and VWAP filters could have generated early sell signals before the crash.

On OCT 9 2025, MORPHOMORPHO-- dropped by 162.1% within 24 hours to reach $1.758, MORPHO dropped by 663.13% within 7 days, dropped by 663.13% within 1 month, and dropped by 663.13% within 1 year.

The recent sharp decline in MORPHO has drawn attention to underlying on-chain liquidity and token distribution dynamics. Recent data highlights a significant outflow from key on-chain wallets, suggesting a potential reallocation of assets by large holders. The movement is notable due to its timing, occurring amidst a broader selloff in the asset class. No new major partnerships, governance updates, or token buybacks have been disclosed during this period, further indicating the drop is driven by internal on-chain behavior rather than external market catalysts.

Technical indicators have pointed toward prolonged bearish momentum. The RSI has remained below 30 for three consecutive days, indicating oversold conditions. However, given the extended duration of the decline, this may signal a deeper structural issue rather than a temporary correction. The asset is currently trading below both its 50-day and 200-day moving averages, reinforcing the bearish trend. Analysts project that without a significant on-chain reversal or off-chain catalyst, the downward trajectory may continue.

Backtest Hypothesis

A proposed backtesting strategy seeks to model the asset’s behavior under various scenarios to determine if a hedging approach could have mitigated losses. The hypothesis is based on a moving average crossover system combined with a volume-weighted average price (VWAP) filter. The model would have generated a sell signal when the short-term moving average crosses below the long-term, and a buy signal if the VWAP indicates a potential reversal. The strategy aims to capture volatility while avoiding noise. If applied to the recent period, the model would have triggered a sell signal ahead of the initial 24-hour drop, potentially offering investors an opportunity to reduce exposure before the rapid decline.

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