SHIB Price Up 0.2% Amid Market Volatility and Privacy Coin Shifts

On NOV 1 2025, SHIB rose by 0.2% within 24 hours to reach $0.00001002, despite a 3.27% decline over 7 days and a steep 52.55% drop over 1 year. The token remains in a mixed performance pattern, reflecting broader volatility in the crypto market. While Zcash (ZEC) and Monero (XMR) have made headlines for surpassing SHIB in market cap, SHIB’s short-term price rise indicates some renewed speculative interest, especially after its modest 0.2% monthly increase.

SHIB’s recent price behavior has been shaped by broader market dynamics. The token has struggled to maintain long-term gains, with a sharp pullback observed in the past 365 days. However, the modest 24-hour and 30-day gains suggest pockets of optimism among retail traders. Analysts note that SHIB’s performance is often tied to broader meme token sentiment and social media-driven trading activity, rather than fundamental developments. In this context, SHIB’s price rise appears to be more of a short-term bounce than a sign of a sustained trend.

Technical indicators used in SHIB trading strategies typically include moving averages, RSI, and volume analysis. Traders often look for confirmation of bullish or bearish patterns after a 5% or greater single-day price swing. These tools help frame potential entry and exit points for strategies that involve short-term trading or event-based buying. However, the effectiveness of such indicators depends on the accuracy and completeness of historical price data—particularly in avoiding gaps or invalid entries that can distort statistical models.

Backtest Hypothesis

To test the potential effectiveness of a strategy based on SHIB’s 5% daily price swings, a backtesting approach was proposed. This strategy would involve buying the asset on days where the price increases by at least 5% from the prior close, holding the position for up to 10 days, and including a 10% stop-loss and 20% take-profit target. The goal is to assess how frequently such a strategy would yield positive returns.

However, the initial attempt to run the backtest encountered two key issues. First, the backtest engine failed to correctly map the historical price data to the test structure, likely due to a formatting or data-linking error. Second, an event-based study (which tracks performance after each qualifying price surge) produced an error caused by zero or missing price entries in the dataset, leading to a division-by-zero error.

To proceed, the data must be cleaned by removing or forward-filling zero-value entries so the system can compute returns safely. Once this is done, the event-based analysis can be rerun, followed by a strategy backtest if the initial results appear favorable. This process allows for a clearer understanding of SHIB’s post-surge performance and whether a 5% threshold is a viable signal for profitable trades.