Analysis of Uncommon Sector Movements: Extreme Sentiment Signals Indicate a Sharp Rebound in Anonymous and Storage Coins

1. Market Background

Recently, market rotation has accelerated noticeably, with less popular sectors showing phased activity. Leading anonymous coins DASH and ZEC initiated the rally first, followed by storage sector representatives AR and FIL, forming a short-term structure driven by “funds low absorption + oversold rebound.”

Meanwhile, mainstream coins BTC and ETH have gradually stabilized in the bottom area, with leverage clearing completed, and market sentiment shifting from extreme panic to cautious observation.

Against this backdrop, the willingness of funds to bet on undervalued tracks has increased, with anonymous and storage sectors becoming the most resilient representatives in this rebound.

2. Correlation Between Sentiment and Price

Based on hourly data, we calculated the Pearson correlation coefficient between the sentiment indicator (Emo_Z) and the next hour’s price change rate.

The results show that ETH and ZEC have the most prominent sentiment correlation, especially ZEC, where sentiment changes are significantly positively correlated with price changes (R=0.527), indicating that the anonymous coin sector reacts more sensitively to market sentiment fluctuations. In other words, when sentiment indicators change sharply, prices tend to respond in the short term with synchronized feedback.

3. Model Logic and Signal Interpretation

The model adopts an Correlation Adaptive Strategy Framework, which automatically switches signal directions based on the different coin types’ sentiment-price relationships:

• Trend Continuation Strategy (Momentum): When sentiment and price are positively correlated (R ≥ 0), rising sentiment is viewed as an increasing momentum signal;
• Contrarian Strategy: When sentiment and price are negatively correlated (R < 0), extreme pessimism can become a potential buy point;
• Thresholds are set at ±2, corresponding to the extreme ends of the sentiment distribution, triggering signals only when market sentiment deviates strongly.

This design allows the model to flexibly switch logic under different market environments, capturing both strong trending opportunities and reversal chances in less popular coins.

4. Backtest Performance of Signals

In the sample period in early November 2025, the model triggered 17 valid signals, correctly predicting 11, with a one-hour ahead price direction prediction accuracy of 64.71%.

Signals mainly concentrated during November 5 to November 7, during the initiation phase of anonymous and storage sectors, especially with ZEC, DASH, AR entering extreme sentiment zones multiple times.

Some typical signals are as follows:

5. Key Conclusions

• The anonymous and storage sectors led the market rotation, showing a clear oversold rebound structure;
• The sentiment indicator Emo_Z in the ±2 zone can effectively identify extreme market states, providing a quantitative reference for stage reversals;
• Funds flowed from mainstream coins to less popular ones, accompanied by rapid sentiment recovery and improved trading efficiency;
• Extreme sentiment values often lead price formation of “resonance turning points,” offering high monitoring value;
• It is recommended to closely track short-term opportunities in high-elasticity sectors like anonymous and storage when similar sentiment extremes occur in the future.

6. Charts Display

The sentiment-price dual-axis charts included in the report clearly show the distribution of signals across different stages for each coin:

BTC_Price_EmoZ_OnEmoZLine:

DASH_Price_EmoZ_OnEmoZLine:

ETH_Price_EmoZ_OnEmoZLine:

• Green Upward Triangle: Buy signals triggered during extreme low sentiment;
• Red Downward Triangle: Sell signals triggered during overheated sentiment.

It can be observed that the anonymous coins’ sentiment curves in early November showed significant turning points, with signals concentrated and having some foresight.

7. Risk Warning

• This report is based on historical data and statistical correlations, and does not constitute any investment advice.
• Cryptocurrency assets are highly volatile; sentiment indicators may lag or distort under extreme market conditions.
• Investors should consider macro liquidity, capital structure, and market expectations comprehensively and operate cautiously.