OPEN drops by 85.64% within 24 hours as trading activity experiences a steep decline

On September 19, 2025, OPEN saw a dramatic drop in its price, plunging 109.42% in the last 24 hours and settling at $0.8564. Over the previous week, the asset lost 1430.14% of its value, and over the past month and year, the declines reached 4017.28%. These sharp losses highlight a swift and severe shift in market sentiment, with no clear indication of a recovery in sight.

OPEN’s price collapse has come during a broader market downturn, but its losses have exceeded those of other leading cryptocurrencies. This steep decline has alarmed investors, especially since the asset had previously shown positive technical patterns, like a clearly defined upward channel that hinted at further gains. The abrupt reversal of these patterns has prompted many holders to reconsider their positions in OPEN, with a noticeable move towards safer assets and stablecoins.

Prior to the downturn, technical analysis of OPEN highlighted the strength of its rising channel and growing bullish momentum. These signals were generally seen as signs that the rally would persist, so the quick shift to a downtrend has been particularly unsettling. Critical support levels have failed, and the lack of immediate buying activity has intensified the pessimistic outlook.

Backtest Hypothesis

A backtesting method was suggested to assess how effective trading signals generated by the previously mentioned technical indicators would have been before the price crash. This approach aims to replicate buy and sell decisions triggered by certain chart patterns and breaks of trendlines.

The simulation starts by spotting an ascending channel in OPEN’s price movements. A breakout above the top of the channel signals a buy, with a stop-loss set at the lower boundary. In contrast, a drop below the lower boundary triggers a short position, using a stop-loss just above the upper boundary.

This approach also employs a time-weighted moving average (TMA) to help filter out short-lived price swings and confirm the persistence of the trend. Positions are only taken when the TMA supports the direction of the breakout, which helps to minimize misleading signals.

Historical data would then be used to model how this strategy would have performed over a chosen timeframe, preferably several months to account for various market environments. The backtest would be judged using metrics like overall returns, Sharpe ratio, and maximum drawdown to gauge the effectiveness of the strategy.