How AI Trading Signals Work

AI trading signals analyze market data across multiple dimensions simultaneously and produce actionable verdicts — faster and more consistently than manual analysis.

The data inputs

• Price and volume — OHLCV data across multiple timeframes (1m, 5m, 15m, 1H, 4H, 1D)
• Derivatives data — options open interest, put/call ratios, funding rates (for crypto)
• Macro indicators — CPI, NFP, PMI, central bank rates, yield curve shape
• Sentiment signals — social volume, news flow, long/short ratios
• Cross-asset correlations — DXY, VIX, bond yields vs equity behavior

How signals are generated

A signal engine processes these inputs through quantitative models. The best systems use an ensemble approach: multiple independent models vote, and disagreement between them flags uncertainty.

Tidava runs 30+ engines per asset and weights their votes by recent accuracy in the current market regime — so a momentum model carries more weight in trending markets than in ranging ones.

What makes a good AI signal?

1. Explainability — you should know why the signal fired
2. Regime awareness — a strategy that works in trends fails in ranges
3. Macro integration — ignoring central bank data causes major misses
4. Risk output — a good signal includes invalidation level, not just direction

Free vs paid AI signals

Free AI signal services often use a single model and lag real-time data. Paid tiers typically add multi-model ensembles, real-time alerts, and Telegram delivery. Tidava offers a free tier with live verdicts and paid plans from $19/month.