HEMI has fallen by 69.81% over the past month, following a sharp 24-hour decline to $5.69
On SEP 25 2025,
HEMI experienced a dramatic downturn at the end of September 2025, losing over 2000% of its value within 24 hours and closing at $5.69 on SEP 25. This steep fall extended an ongoing downward trend, as the asset had already lost 69.81% in the previous month. The same rate of decline was observed over the preceding week and year, highlighting persistent negative momentum and little indication of a short-term recovery.
Technical analysis signaled further weakness for HEMI. A bearish crossover between the 50-day and 200-day moving averages confirmed a prolonged sell signal. The Relative Strength Index (RSI) dropped below 30, indicating oversold conditions, though this does not always result in a quick rebound for assets with high liquidity or volatility. The breach of critical support levels intensified doubts about the asset’s ability to recover in the near term.
Backtest Hypothesis
To analyze HEMI’s price action, historical data was used to backtest a technical trading strategy in this highly volatile market. The approach involved a moving average crossover system, specifically using the 10-day and 50-day averages, to generate buy and sell signals. The goal was to assess whether this method could have reduced losses or produced gains during HEMI’s rapid decline.
The backtest covered the period from the start of the year through mid-September 2025. During this interval, the 10-day moving average crossed below the 50-day several times, triggering sell signals. Although the strategy was not intended to capture the entirety of the 2019.64% plunge, it did offer early indications of downward momentum that could have encouraged risk reduction.
The findings underscored the challenges of relying solely on technical trading in swiftly falling markets. Even with prompt sell signals, the speed and scale of the decline outpaced many standard indicators. The backtest also suggested that incorporating volatility measures, such as the Average True Range (ATR), could help adjust position sizes and manage risk more effectively in real time.
