Short answer
A trading signal is a measurable input used to inform a trading decision. It can rank assets, trigger entries, adjust sizing, identify regimes, or warn that a trade should be avoided under the current conditions.
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Topic cluster / Canonical learn hubsWhat is a trading signal?
Define trading signals, see examples from crypto markets, and learn how signals become strategy building blocks rather than standalone predictions.
Reviewed by Alphora Research
Updated June 20, 2026
What to remember
- Ranking signals compare assets or markets against each other
- Trigger signals decide when a rule should activate
- Sizing signals scale exposure up or down
- Risk signals warn that a trade should be reduced or avoided
Signals are not strategies by themselves
A signal might say one market is more attractive than another, but a strategy also needs sizing, risk limits, portfolio construction, execution rules, and conditions for standing down.
Common signal types
Signals can describe expected return, risk, liquidity, regime, execution quality, or confidence. A good research workflow names which job the signal is doing before it is combined with other rules.
- Ranking signals compare assets or markets against each other
- Trigger signals decide when a rule should activate
- Sizing signals scale exposure up or down
- Risk signals warn that a trade should be reduced or avoided
- Context signals describe the environment around the main idea
Crypto signal examples
Crypto signals can use funding rates, perp basis, liquidity imbalance, realized volatility, cross-sectional momentum, order book depth, or regime filters. The important question is whether the signal remains useful after costs, constraints, and risk are included.
How to document a signal
A signal should be documented as a repeatable object, not a screenshot. The documentation should explain the measurement, data dependencies, expected use, known weaknesses, and how the signal interacts with other portfolio rules.
- What the signal measures
- What data it needs and when that data becomes available
- Where it historically helped or failed
- Which costs or liquidity constraints matter most
- Whether it overlaps with existing signals
How Alphora fits in
Alphora treats signals as reusable research components. Catalogue pages explain what each signal measures, where it can fail, and how it can fit into a broader systematic trading workflow.