PLUME drops 16.29% amid heightened market volatility and negative technical signals

On September 25, 2025,

saw its price tumble by 16.29% in just one trading day, dropping to $4.102. Over the past 24 hours, the token plummeted by 335.29%, and over the last week, it suffered a dramatic 1,263.25% loss. Despite these sharp declines, PLUME has posted a robust 2,426.89% gain in the previous month and an overall increase of 983.21% over the last year.

The steep drop in PLUME’s price during the session highlights mounting market stress amid uncertain macroeconomic conditions and persistent bearish sentiment. Short-term market participants are responding to deteriorating technical signals, including the RSI and MACD, both of which have shifted into negative territory. The RSI has fallen under 30, signaling oversold status, while the MACD has crossed beneath its signal line, further confirming the bearish outlook. Furthermore, the asset has breached significant support zones that previously helped stabilize its price, raising the chances of continued declines.

These recent developments have drawn greater attention from algorithmic traders and quantitative hedge funds, who are now repositioning in expectation of a prolonged downtrend. These market players typically rely on technical analysis and backtesting to optimize their trading strategies. At present, traders are focusing on the $4.00 mark as a possible short-term support; a move below this threshold could trigger additional technical selling.

Backtest Hypothesis

A backtesting approach has been implemented to assess a group of technical indicators for potential trade entry and exit points, utilizing PLUME’s historical price movements. This method combines moving averages, RSI, and MACD crossover signals. The main concept is to initiate a short position when the 50-period moving average drops below the 200-period moving average (death cross), the RSI dips under 30, and the MACD line falls beneath the signal line. Exits are triggered if any of these indicators shift back to bullish, or if the price hits a predetermined stop-loss below a critical support level.

This approach aims to take advantage of bearish momentum while reducing risk from sudden market reversals. By applying the strategy to historical data, the goal is to determine whether these signals can be effectively used in real-time trading. The results of the backtest will indicate if this combination of indicators successfully identifies downside opportunities and avoids misleading signals during upward trends.