OPEN -121.86% in 24 Hours Amid Sharp Decline in Liquidity and Market Sentiment

On SEP 13 2025, OPEN dropped by 121.86% within 24 hours to reach $0.9128, OPEN dropped by 3673.8% within 7 days, dropped by 3673.8% within 1 month, and dropped by 3673.8% within 1 year.

The sharp decline in OPEN’s price has been attributed to a broad withdrawal of liquidity and shifting investor sentiment, according to recent market activity. Multiple on-chain analytics tools have detected a significant outflow of funds from OPEN-related wallets and pools. The asset has seen a steady erosion of its trading volume and active addresses over the past several days, compounding the downward pressure. Market participants have pointed to a lack of new investment inflows and growing risk aversion as key factors behind the sell-off.

Technical indicators have painted a bearish picture for OPEN in the near term. The 50-day and 200-day moving averages have both crossed below key support levels, indicating a breakdown in trend continuation. Additionally, the Relative Strength Index (RSI) has sunk into oversold territory, suggesting limited upside potential in the short term. These metrics have been closely monitored by market analysts as potential triggers for further downward momentum.

Backtest Hypothesis

A backtesting strategy has been proposed to analyze the effectiveness of technical signals in navigating the recent volatility in OPEN. The strategy assumes a long position is initiated when the 50-day moving average crosses above the 200-day moving average (a bullish “golden cross”), and a short position is triggered when the opposite occurs (a bearish “death cross”). Stop-loss and take-profit levels are dynamically adjusted based on the 20-day volatility range. The hypothesis is that the death cross observed in early September would have signaled an optimal short entry point, aligning with the subsequent 121.86% drop in 24 hours. The backtest aims to evaluate the strategy’s performance over the past 30 days, using historical OHLC (open-high-low-close) data as input. The test will also measure drawdowns and risk-adjusted returns to assess robustness.