Updated: 2026-02-20
In trading, Fill price is the actual executed price of your order (which can differ from your intended price). This glossary entry explains why fill price matters, how traders use it, and how to track it with evidence instead of vibes.
Quick definition
Fill price: the actual executed price of your order (which can differ from your intended price).
Fill price is the actual executed price of your order (which can differ from your intended price). The practical version is: can you define it as a field you can log and audit later?
Most trading terms become confusing when they are used as vibes instead of variables. Your goal is a definition that helps you decide size, stop, entry timing, or whether to skip the trade.
Traders sometimes confuse Fill price with mark price. Treat them as separate variables in your journal so your reviews stay honest.
Fill price is where execution becomes real. A setup can be correct but still lose money if your average fill is consistently worse than your model assumes.
If Fill price never changes your decision, it is just jargon. The term earns its place when it improves your process consistency under real market pressure.
A useful mental model: plan first (risk and invalidation), execute second (order type and fills), review last (tags and metrics).
Use it to make one decision pre-trade. Example decisions: where the stop goes, whether to take partials, how to scale size, or whether conditions are too thin to trade.
Write the rule in one sentence, then run it consistently for a week. Consistency matters because it creates comparable data for review.
If the rule fails, adjust slowly. Do not rewrite the whole system after one bad session.
Store intended price and actual average fill price for each order. Track slippage in bps and dollars by venue, symbol, and time of day so you know when execution degrades.
Use tags so you can slice results by regime and behavior state. The same term behaves differently when volatility changes or when you are fatigued.
Your review question should be binary: did this variable improve outcomes or reduce rule breaks? If not, simplify.
You send a market buy at 100 but your average fill prints 100.12 due to thin liquidity. That 12 bps gets paid again on exit if you also market out.
The point of an example is not to predict price. It is to show what you would log before the trade and what you would audit after the trade.
Assuming the chart price is the price you got filled at, especially during fast moves.
The fastest way to improve fill price is to remove one failure mode at a time. If you try to fix everything, you will fix nothing.
Fill price matters most when volatility is high and the book is thin. That's where small execution errors compound into expectancy drag.
Before you trade, decide what matters more: price control (limits) or fill certainty (markets/stops). Then trade the choice consistently for one week so your data is comparable.
If you change order types every time you feel stressed, your metrics will lie to you.
Fill price is the actual executed price of your order (which can differ from your intended price). In practice, it matters when it changes a concrete decision like size, stop placement, or whether you skip a trade.
They are related but not identical. In your journal, track Fill price as its own variable and treat mark price as a separate context factor so you can audit each cleanly.
Store intended price and actual average fill price for each order. Track slippage in bps and dollars by venue, symbol, and time of day so you know when execution degrades.
Assuming the chart price is the price you got filled at, especially during fast moves.
See plans and run one weekly review loop with Tiltless: edges, leaks, and enforceable next actions.
