ZKC Plummets 7080.67% Year-to-Date Amid Sharp Liquidity Decline

Generated by AI AgentAinvest Crypto Movers Radar
Thursday, Oct 9, 2025 5:09 am ET1min read
ZKC--
Aime RobotAime Summary

- ZKC plummeted 7080.67% year-to-date by Oct 9, 2025, with 3711.6% monthly and 1024.21% 24-hour declines.

- Liquidity collapse and massive outflows signal lost investor confidence, with on-chain metrics showing reduced active addresses.

- Technical indicators confirm prolonged bearish trends, as RSI nears oversold levels without triggering price recovery.

- A backtesting strategy tests Fibonacci-based trading rules with 10% stop-loss and 15% take-profit targets amid extreme volatility.

On OCT 9 2025, ZKCZKC-- dropped by 1024.21% within 24 hours to reach $0.2757, ZKC dropped by 1578.14% within 7 days, dropped by 3711.6% within 1 month, and dropped by 7080.67% within 1 year.

The token experienced a severe drop in liquidity, with trading activity collapsing in recent months. Over the last 30 days, ZKC’s price trajectory has shown minimal recovery, and on-chain metrics indicate a sharp reduction in active addresses and wallet interactions. The market appears to be dominated by large-volume outflows, signaling a loss of confidence among core participants.

Technical indicators further highlight the depth of the sell-off. The 50-day and 200-day moving averages have remained in a prolonged bearish alignment, with the RSI hovering near oversold territory. However, this has failed to trigger any meaningful bounce, suggesting the market is not responding to typical reversal cues. Analysts project that unless there is a significant intervention or announcement, the asset is likely to remain under pressure.

Backtest Hypothesis

A proposed backtesting strategy attempts to model the asset’s recent behavior using historical price levels and volume patterns. The approach involves identifying key support and resistance zones based on Fibonacci retracement levels and testing the efficacy of trend-following and mean-reversion strategies. The backtest assumes a fixed stop-loss at 10% and a take-profit target of 15% above key support levels. It also incorporates a volatility-based position sizing mechanism, which would scale in or out of positions based on daily ATR values. The aim of this strategy is to validate whether mechanical trading systems can capture value in a deeply bearish environment where manual intervention may be less effective.

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