Direct costs: what they are and why they matter
Trading signals are rules or alerts that describe when a market participant may enter or exit a position. The signal itself is not the outcome; the outcome depends on the prices actually paid and received after costs. Direct costs are charges that reduce the difference between entry and exit prices in a predictable way, given the trade size and the execution prices.
Common direct cost examples include the bid–ask spread and explicit commissions. The spread is the built-in difference between the buying and selling price quotes. Commissions are separate fees charged by an execution venue or provider. If a signal triggers a buy and later a sell, the realized move must be large enough to cover these deductions; otherwise, the costs can turn a profitable “paper” movement into a flat or losing result.
Indirect costs: timing, execution, and holding effects
Indirect costs are effects that change the prices you actually get or the economics of holding a position, even if there is no obvious commission line item. These costs can vary with market liquidity and speed, and they often appear as slippage or altered holding economics.
Slippage is the gap between the intended execution price and the actual filled price. For example, if your signal assumes execution at the current quote but the order fills after the market moves, the entry becomes worse (or the exit becomes worse) compared with the signal’s implied pricing. Timing costs also matter: if the signal is generated using one time reference but orders execute at another, you may consistently trade at slightly different conditions than assumed.
Holding effects can also be indirect costs. For some leveraged or derivative arrangements, the cost of maintaining a position can include financing or rollover components that accrue over time. Even when you do not see them as a “transaction fee,” they affect net results of trades that stay open across sessions.
Mechanics: assumptions behind a cost-aware signal
To understand how costs affect signals, separate stable mechanics from variable conditions. Stable mechanics are the signal’s decision logic: when it triggers, what type of order it assumes (market vs. limit), and what it expects for fill behavior. Variable conditions include spread size at the time of execution, market liquidity, volatility, and any time-dependent holding economics.
A simple cost-aware calculation requires stating assumptions clearly. For instance, assume a signal enters with one-way costs of 1 unit per trade due to spread/commission and assumes an exit with the same 1 unit. If the gross price movement between entry and exit is 2 units, then net may be near zero before slippage and any holding effects. If actual spread is higher or slippage occurs, net becomes negative. These calculations are not predictions; they are consistency checks.
Evidence and example checks (without relying on future outcomes)
Because historical relationships do not guarantee future results, verification should focus on whether a signal is robust to realistic cost modeling. A practical example is to take the same signal rules and compute outcomes under multiple cost scenarios. Vary spread from “typical” to “wider,” add plausible slippage, and include a holding cost estimate for trades that last longer than one day.
If performance changes drastically when costs are slightly increased, the signal is cost-sensitive. If performance improves only when you assume unrealistically low costs or immediate fills, that is a red flag: the signal may be exploiting assumptions rather than capturing something that survives realistic execution.
Limitations and failure modes you should watch
A material limitation is execution uncertainty. Signals often assume that orders fill near a quote at the time of the alert, but real fills can differ due to fast markets or low liquidity. Another failure mode is partial fills: you may not receive the full intended quantity immediately, changing average entry price.
Costs can also change over time. Even without changing the signal rules, spread and liquidity can widen during certain market conditions, which can increase slippage. Holding effects can also make results time-dependent, so the same entry/exit logic can behave differently across trade durations.