What trading signals are, and what they are not
Trading signals are messages or instructions that claim to indicate a potential opportunity to enter or exit a trade. The key misunderstanding is treating a signal as an automated promise about future price movement. A signal generally cannot control market volatility, slippage, spreads, or how quickly an order is executed. Another frequent error is confusing different layers of a “signal”: the idea (the method that produces a recommendation) versus the implementation (the trader’s or platform’s execution details).
Common mistakes and why they matter
One mistake is ignoring the difference between a signal’s generation and its execution. Even if a method forecasts a direction, real trading involves costs and delays. If execution differs from the assumed trade entry and exit (for example, due to market gaps, partial fills, or variable transaction costs), the realized outcome can diverge from any backtest or description.
A second mistake is assuming timing is exact. Many signals describe an estimated moment or a decision rule, but markets do not “pause” for signals to arrive. If the signal is produced at one time and acted on later, the relevant price may already have changed.
A third mistake is relying on historical performance without defining the conditions. Backtests often rely on assumptions such as liquidity, spreads, order fill logic, and whether data is accurate and complete. Historical relationships do not automatically establish future results, especially when volatility, volatility clustering, or regime shifts change how strategies behave.
Evidence and example of a failure mode
A neutral way to see where signals can fail is to track a simple assumption chain: (1) the signal triggers under a rule, (2) an order is placed at an assumed price, (3) costs are applied consistently, and (4) exits occur as specified. Any break in that chain can alter results. For example, if a signal description assumes a fixed spread but actual spreads widen during news or low-liquidity hours, the effective entry and exit prices change, which can turn a strategy that “looked profitable” on paper into a losing one in practice.
Another failure mode is data mismatch. If the signal uses one data source, timeframe definition, or contract specifications while the trader executes using different settings, the method may not produce the same results.
Limitations, risks, and neutral checks
Trading signals carry uncertainty. Outcomes vary with market conditions, execution quality, transaction costs, and practical constraints such as order types and trading hours. A signal can also be incomplete: some descriptions provide the direction but omit necessary details like exact entry/exit rules, risk controls, and what to do in case of ambiguous conditions.
Use neutral checks, not certainty checks. The “klaarcriterium” is satisfied when you can independently explain:
- what rule generates the signal (the mechanism),
- what assumptions are used for example calculations (prices, timing, costs),
- what conditions cause the method to stop working (a material limitation).
If a claim cannot be translated into explicit, testable rules with clear assumptions, treat it as a broad suggestion rather than a dependable instruction.
As “rode vlaggen,” watch for vague descriptions (no entry/exit logic), reliance on unspecified backtesting assumptions, and performance statements that do not specify the measurement method. Finally, demand the “bewijs of document” level of clarity: enough information to reproduce the logic and verify whether the assumptions are realistic for your execution context.