Signals
What is a Signal?
In Spica, a signal refers to a token event (migration, social activity and more) that triggers an analysis pipeline. These signals are crucial for gaining insights into a token's market behavior and performance. When a signal is triggered, a series of metrics are calculated to help evaluate the token's activity, its distribution, and other important characteristics at that specific point in time. The analysis pipeline provides a structured breakdown of key aspects, offering a comprehensive view of the token's current state and potential.
Core Metrics
Every signal is associated with a set of core metrics that are used to evaluate the token. These metrics offer a snapshot of the token’s characteristics at the time of the event, providing valuable insights into its market dynamics.
% Bundled
The % Bundled metric measures the percentage of the token supply that was bought in transactions bundled with the mint transaction. In other words, it reflects how much of the token’s supply was acquired by participants during the minting process. When referring to dev/creator holdings, other platforms often consider only the amount bought at mint by the token creator in the same transaction. However, some creators use bundle transactions to buy the token with other wallets alongside the mint transaction. The % Bundled metric captures the full picture so you can accurately evaluate the dev holdings and its impact on concentration. A high percentage could suggest that the development team or insiders have retained a large share of the tokens, which might affect the token's future liquidity and market behavior.
Top 15%
Top 15% reflects the percentage of the token supply that is held by the top 15 token holders. It provides a view of the token’s distribution, highlighting whether a significant portion of the supply is controlled by a few large holders or whether the distribution is more decentralized.
Holders > 5%
This metric counts the number of wallets that hold more than 5% of the token's total supply. A large number of holders with such significant holdings could indicate centralization risks or the potential for market manipulation, while fewer such holders could suggest a more decentralized token.
Website, Socials, DEX Paid, DEX Boost
These attributes provide insights into the token’s marketing footprint (as seen on Dex Screener at event time):
- Website — whether the token has a website displayed.
- Socials — whether the token lists social media links.
- DEX Paid — whether the token is paying Dex Screener to feature a banner.
- DEX Boost — whether the token has active boosts.
These factors help evaluate the token's community engagement and visibility.
Signal-Specific Metrics
Migration Signals
For migration events, an additional metric called Time to Migration is included. This metric measures how long the token took to migrate, computed as the difference between migration time and creation time.
Telegram Calls
For Telegram calls, an additional property, Caller Name is included.
Performance Metrics
Spica computes performance metrics for each signal over 3 time intervals. These metrics track the token’s price performance after the event and are crucial for understanding its short-term market behavior.
Time Intervals
Performance metrics are computed at 5-minute, 10-minute, and 1-hour intervals. At each interval, the min, max, and end return of the token’s price are computed, giving a detailed view of how the token’s price fluctuated following the signal.
Calculation Timing
The performance metrics are evaluated starting from 10 seconds after the event time. This 10-second window accounts for the time it takes for market participants to react to the event and buy the token, providing a more accurate picture of post-event performance.
Key Considerations
- All attribute values (e.g., DEX banner/boost) are recorded as of the event time. If these change later, the metric is not retroactively updated. This is to allow analysis of token characteristics at event time.
- Performance metrics intentionally start 10 seconds after the event to reflect realistic reaction time and improve accuracy.