AVNT Price Rises 122.65% in 24 Hours Amid Market Volatility

On SEP 26 2025, AVNT surged by 122.65% within 24 hours to reach $1.5851, marking a dramatic reversal after a steep 3186.28% drop over the preceding seven days. Despite this recent decline, the token has shown resilience, with a 9869.14% increase recorded over both the past month and the past year. The price swing underscores the volatile nature of the asset and has drawn renewed attention from traders and analysts.

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The recent spike follows a period of intense selling pressure and uncertainty. Over the past week, AVNT experienced a significant sell-off, which many analysts believe was driven by algorithmic trading patterns and a shift in investor sentiment. However, the sharp correction appears to have triggered a rebound as short-term traders and automated systems capitalized on the drop. No major corporate announcements or regulatory changes were reported during this period, suggesting the movement was primarily market-driven.

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Looking at the technical indicators, AVNT has broken above key resistance levels following the recent upswing. The RSI has moved into overbought territory, while the MACD line crossed above the signal line, indicating potential bullish momentum. Traders have begun to closely monitor whether the asset can sustain its current trajectory or face a pullback. Analysts project that continued volatility may persist due to the high leverage of speculative positions.

Backtest Hypothesis

The recent price movement has spurred interest in evaluating algorithmic strategies based on AVNT’s behavior. A backtest strategy was developed to assess whether a specific technical trading approach could have captured or predicted the recent price action. The strategy was built using historical AVNT data and tested against a defined set of rules focused on identifying momentum shifts and volatility spikes.

The core of the backtest involved entering a long position when the price crossed above a 20-period moving average and the RSI moved above 50, with an exit triggered when the RSI hit overbought levels and the MACD line crossed below the signal line. Stop-loss and take-profit levels were dynamically adjusted based on ATR readings to manage risk. This method was applied to historical data to simulate returns and assess robustness.

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