CHESS +273.08% 24H Due to Short-Term Volatility Spike

On SEP 2 2025, CHESS rose by 273.08% within 24 hours to reach $0.06876, while experiencing a 421.69% drop over the past week, a 143.29% decline over the past month, and a staggering 6147.73% fall over the past year. The recent sharp daily rebound has drawn attention from traders and analysts who are closely examining the underlying catalysts.

The sudden upward move appears to be driven by a combination of short-term speculative activity and potential order imbalances, though no official announcements or fundamental developments were reported during the period. Market participants are now scrutinizing the sustainability of the move, given the stark contrast between the 24-hour gain and the longer-term bearish trajectory. Analysts project that such sharp corrections and rebounds are more typical in highly liquid and speculative digital assets, where sentiment can shift rapidly.

Technical analysts have noted a brief but notable break above key resistance levels in the immediate aftermath of the 24-hour surge. However, these movements have not yet translated into a reversal of the longer-term trend. The asset remains well below critical support levels that were breached in previous weeks, raising questions about whether the rally will hold or serve as a short-lived bounce within a broader downtrend.

Backtest Hypothesis

Given the observed volatility and potential for rapid reversals, a backtesting strategy has been proposed to evaluate the effectiveness of a mean-reversion model. The hypothesis is that short-term price spikes followed by sharp retracements could be profitably traded using a combination of RSI and moving average crossovers. Specifically, the strategy would trigger long entries when RSI falls below 30 and a short-term moving average crosses above a longer-term average, with stops placed just below key swing lows. Conversely, short entries would be triggered when RSI exceeds 70 and the moving average crosses below, with stops set above recent swing highs. This approach is designed to capture momentum in the wake of volatility spikes while mitigating exposure to longer-term declines. The model will be tested using historical data to determine whether it could have generated consistent returns amid the recent erratic price behavior.