EIGEN +588.24% in 24 Hours Due to Strong Short-Term Volatility

On SEP 2 2025, EIGEN experienced a dramatic 588.24% price increase within 24 hours, climbing to $1.218, driven by a surge in market sentiment and short-term speculative activity. Despite this sharp rise, the token has faced a broader downward trend over the 7-day period, with a total decline of 526.32%. Over the past month, EIGEN has rebounded with a 108.97% gain, showcasing its volatility and potential for rapid price swings.

The recent movement in EIGEN’s price has drawn attention from both retail and institutional participants. Technical indicators suggest the token is operating in a highly volatile and non-linear trading pattern. This behavior is often observed in emerging digital assets where liquidity can shift rapidly and trading dynamics are still evolving. Traders have noted a significant increase in the number of short-term orders, pointing to an active retail-driven market dynamic.

Technical analysts have examined EIGEN’s chart patterns and have identified several key indicators influencing the recent surge. These include an unusually high volume-to-price divergence and a strong positive divergence in momentum oscillators. While the 24-hour jump was dramatic, it has not yet triggered a broader breakout in the medium-term trend, which remains bearish. Analysts project that the 1-year trajectory of EIGEN, marked by a 6572.89% drop, suggests structural challenges that may not be overcome by short-term speculative buying.

Backtest Hypothesis

A proposed backtesting strategy seeks to capture the short-term volatility seen in EIGEN’s recent price action. The strategy is based on the use of momentum oscillators and volume divergence signals. It operates under the hypothesis that extreme divergences in these indicators can be used to time high-probability entries in assets with high liquidity and short-term price elasticity. The model would trigger a long position when a positive momentum divergence occurs in conjunction with a sharp rise in volume, as observed during the 24-hour surge. Exit signals are based on moving averages and trailing stops to capture gains while limiting exposure to potential reversals. This approach is designed to be applied to other similar assets with comparable volatility profiles, using historical price data to simulate and validate performance outcomes.