Direct answer: what data you need
To assess a stop limit order, gather (1) the order’s own parameters, (2) the execution rules that govern how the platform handles triggers and fills, and (3) the practical cost and constraint inputs that can change results. Because outcomes depend on timing and market movement, you also need checks that confirm your information is complete, internally consistent, and not stale.
Mechanism and definition: what a stop limit order depends on
A stop limit order combines two price levels and an activation rule:
- Stop price: the level that “triggers” the order.
- Limit price: the maximum (or minimum, depending on side) price the order will execute at.
- Side (buy or sell): determines whether the stop triggers when price moves up or down.
- Time-in-force: how long the order stays active (for example, until a date, or for a session).
- Quantity: the requested size, which matters for partial fills.
- Order handling details: whether the platform treats the order as a single order or can rest in a queue until conditions are met.
Stable mechanics you can state without market data: the order becomes eligible when the stop condition occurs, and then it places a limit constraint on execution. What you must source as “variable” data is how your specific execution venue and platform translate those settings into an actual fill process.
Evidence and example: checklist of inputs to assess before judging outcomes
Use a structured set of inputs and verify each one’s provenance and timeliness.
1) Order-parameter inputs (the “what you set”)
Collect:
- Stop price, limit price, side, and quantity.
- Time-in-force.
- Any platform-specific fields (for example, how the platform defines the stop condition, or whether it uses last traded price vs. another reference).
Assumption statement (for calculations or scenario reasoning): if you compare scenarios, declare your assumption about reference price and whether spreads widen during activation.
2) Execution-rule inputs (the “how it runs”)
Collect from official documentation or the platform’s order-entry notes:
- Trigger definition (what price stream activates the stop).
- How the limit applies after activation.
- Whether the order can be rejected or cancelled automatically under certain conditions.
- Any rules about partial fills, minimum order size, and price increments.
3) Cost and constraint inputs (the “what can change the fill”)
Even without real-time market data, you should identify what cost components and constraints you may need to model:
- Transaction costs (fees/commissions) as documented by the venue/provider.
- Spread behavior assumption (do not assume it stays constant).
- Potential for slippage between the moment the stop triggers and the limit becomes effective.
Quality check: ensure your inputs use consistent units (price increments/tick size) and consistent reference definitions.
4) Timeliness and staleness checks
If you are using any historical or displayed price information, label it as not real-time and treat it as a comparison reference only. Verify:
- When the information was captured.
- Whether the platform data you use is the same reference used by the stop condition.
Limitations and failure modes (material risks to expect)
Stop limit orders can fail to execute even when the market “moves toward” the stop price. Key limitations include:
- Activation timing vs. execution price: by the time the stop condition is met, the market may have moved beyond the limit, preventing fills.
- Gaps and fast moves: sudden jumps can move prices from trigger to beyond the limit without resting at an executable price.
- Partial fill and residual exposure: if quantity cannot be fully executed within the limit constraint, part may fill while the rest remains unfilled or cancelled depending on rules.
- Data-reference mismatch: using a different price reference in your assessment than the platform uses for stop activation can invalidate conclusions.
Rode vlaggen (red flags): missing time-in-force, undefined stop reference, inconsistent price increments, or mixing stale quotes with current rule interpretations.
Verification and next question: how to confirm the facts you used
To independently verify what you need, cross-check:
- Your stop-limit parameter definitions against the platform/venue documentation.
- The stop trigger reference definition (the exact price basis).
- The execution behavior for partial fills, time-in-force handling, and order rejection conditions.
- Any unit constraints like minimum size and price increment rules.