What Makes a Trading Signal Specific Enough to Use?
Specificity means you know the symbol, bias, approximate entry, invalidation, and intended hold style. Vague tips—“tech looks strong”—are commentary, not signals. A good signal lets you calculate shares from risk amount to stop distance within seconds. If you must invent the stop after the alert, the signal is incomplete or you are improvising outside plan. Specificity also means the signal maps to one strategy tag in your journal.
Reject alerts that force you to invent missing risk parameters under time pressure.
Why Does Timing Quality Matter as Much as Direction?
A correct direction at the wrong time destroys risk-reward—chasing extended moves or entering into known illiquid windows. Good signals arrive early enough for planned entry logic (break, retest, open trigger) and late enough that the setup is real. Session context matters: opening-drive signals differ from midday mean-reversion. Timing quality shows up in your fill statistics and average adverse excursion, not just win rate.
Track when signals fire; prune templates that cluster in your historically worst window.
How Does Embedded Risk Define Signal Quality?
Quality signals acknowledge where the idea is wrong. Stops and targets—or at least a ranked framework implying risk—let you compare expectancy apples-to-apples. A high-probability scalp with terrible payoff may be inferior to a lower-probability swing with clean asymmetry. Liquidity is risk: wide spreads and thin books degrade even clever models. Good signals favor tradable names under your account constraints.
Score setups by expectancy and dollar risk first, not by how exciting the chart looks.
What Evidence Should Support a Signal You Trust?
Evidence includes sample size, out-of-sample or walk-forward results, cost assumptions, and performance across regimes. Anecdotes and one sensational week are not evidence. For discretionary confirmation signals (pattern plus volume), evidence is your logged hit rate under identical rules. For AI and algorithm signals, demand transparent metrics or run your own forward test. Confidence without evidence is charisma; traders need numbers.
Set a minimum sample before increasing size—streaks are not samples.
How Do You Operationalize “Good Signal” Criteria Daily?
Maintain a written checklist: liquidity floors, maximum risk, structure confirmations, news gates, and strategy tags allowed today. Grade inbound signals pass/fail against that list. Review weekly which fail reasons dominate—spread, extension, conflicting timeframe—and tighten filters upstream when possible. A good signal culture is selective: you want fewer alerts that usually deserve a chart open, not more alerts that train you to ignore everything.
If you routinely skip most alerts for the same reason, encode that reason into the filter.