User Signals: Your Custom Rules, Consolidated on the Dashboard

Your Own Signals Are Your Edge

The pre-built indicators on alphactor.ai are useful, but the most durable edge usually comes from rules you've created yourself — a specific combination of factors that matches your thesis and that no one else is screening for the same way. That's where the User Signals infrastructure fits: you build a rule once, it runs continuously against your universe, and the dashboard shows you which names are hitting it right now.

What the User Signals Card Shows

The User Signals card lists every rule you've defined (across the screener, custom alerts, and conviction-based filters), along with the names currently hitting each rule, the time since the most recent trigger, and a trailing 30-day hit count. A performance indicator shows the historical win rate of the rule when its prior triggers are followed through — real feedback on whether the rule actually does what you built it for.

Making Rules That Actually Work

Three disciplines separate useful rules from noisy ones. First, fewer, deeper rules beat many shallow ones — a single three-condition rule with clear thresholds outperforms six loose single-condition rules in production. Second, review hit rates monthly: rules with hit rates > 0.5/day are usually too loose to be actionable; 1-3 hits per week tends to be the sweet spot for discretionary follow-up. Third, archive, don't delete — rules that didn't pan out are valuable training data for your next iteration; store their historical output rather than wiping them.

Where It Fits

User Signals connects to the Screener (where rules are defined) and Recent Alerts (where rule triggers appear alongside price/volume alerts). Combine with the Watchlist — rules that repeatedly flag the same names are telling you those names belong on your watchlist permanently.

Open the User Signals card → /app