BCH -12.15% in 7 Days Amid Volatile Short-Term Movement

On NOV 6 2025, BCH dropped by 0.49% within 24 hours to reach $487.7, BCH dropped by 12.15% within 7 days, dropped by 9.05% within 1 month, and rose by 12.01% within 1 year.

The recent short-term volatility in BCH reflects broader uncertainty in the broader digital asset markets. While the 24-hour decline appears moderate, the 7-day performance of -12.15% signals a sharper correction. Over the same period, the 1-year cumulative return remains positive at 12.01%, indicating a degree of resilience in the underlying fundamentals. This contrast between long-term and short-term performance underscores the market's mixed sentiment and the influence of transient macroeconomic developments or algorithmic trading activity.

From a technical perspective, the drop into the mid-$480s has brought BCH closer to key support levels that have historically been significant. The 1-month decline of 9.05% has further reinforced these levels, potentially setting the stage for a near-term reversal or consolidation. Analysts project that sustained trading below $480 could invite further downward pressure, but the long-term chart remains above critical moving averages, suggesting continued investor confidence in the asset's future value.

Backtest Hypothesis

Given the recent volatility and the pronounced drop in BCH, a backtesting strategy centered on price shocks can provide insight into potential recovery patterns. Specifically, the behavior of BCH after a -10% daily drop could be analyzed using historical price data to evaluate the average and distribution of returns over subsequent periods. This approach aims to measure whether such drops historically lead to rebounds within specific time horizons and determine optimal holding periods for potential gains.

Unfortunately, the “event_backtest_engine” module is presently throwing two hard-errors (“NameError: Dict is not defined” and a follow-on “ZeroDivisionError”). Because the failure is occurring inside the engine’s internal code, simply retrying with different parameters will keep producing the same result. Your options:

1. Wait for the module to be hot-fixed
   We can re-run the identical request once the backend is patched.

2. Implement a manual fallback calculation
   I can pull the raw BCH price series (already downloaded) and compute, for every -10 % daily drop, metrics such as: – Next-day, +3 d, +5 d, +10 d and +20 d average return
   – Distribution of returns (median, st.dev., win-rate)
   – Best holding-period after the shock
   Results would be returned as a statistical table instead of an interactive chart.

3. Redesign the analysis as a trade-strategy back-test
   For example, buying on the day after a 10% drop and selling after N days or on a 15% rebound using the “strategy_backtest_engine”. This path uses a different backend and is currently operating normally.

Please let me know which path you’d prefer (or suggest another), and I will proceed accordingly.