ACX Dropped 88.37% in 24 Hours Amid Sharp Downturn

On SEP 6 2025, ACX dropped by 88.37% within 24 hours to reach $0.133, ACX dropped by 665.74% within 7 days, dropped by 1156.37% within 1 month, and dropped by 7618.54% within 1 year.

The collapse of ACX has raised concerns among investors and market analysts. The token, which had previously shown signs of volatility, has now experienced an unprecedented sharp decline across multiple timeframes. The 24-hour drop of 88.37% represents one of the most severe corrections in recent history, with the token’s price plummeting to $0.133.

Technical indicators have confirmed a bearish outlook for ACX. The Relative Strength Index (RSI) has fallen into oversold territory, while the Moving Average Convergence Divergence (MACD) has shown a consistent bearish crossover. These signals have historically indicated a continuation of downward momentum, suggesting that further losses may be in the offing. Analysts project that the market could remain in a bearish phase in the near term as key support levels are tested.

The sharp price action has also affected the token’s trading sentiment. Liquidity has thinned, with fewer buyers stepping in despite the significant price decline. The absence of a clear catalyst for the drop has led to speculation about potential off-chain events, though no official statements have been issued. Market participants are now closely watching for any developments that might signal a reversal in sentiment.

Backtest Hypothesis

A backtesting strategy has been proposed to evaluate potential trading signals in a similar market environment. The strategy is based on a set of predefined technical conditions that aim to capture momentum shifts in highly volatile assets. Specifically, it triggers a sell signal when the RSI dips below 30 and the 50-day moving average crosses below the 200-day moving average—a classic bearish crossover. A stop-loss is placed at a fixed percentage below the entry point, while a take-profit target is set at a defined Fibonacci level.

This hypothetical strategy aims to simulate a trader’s response to the bearish conditions observed during ACX’s recent downturn. By applying this framework to historical data, the backtest would assess the potential for profit or loss under similar price dynamics. The results could provide insight into the effectiveness of algorithmic trading approaches in volatile environments and help traders refine their risk management techniques.