Maker vs Taker: How Fees Change Your Break-even
What maker and taker mean
Maker taker is a fee model where the platform charges different fees depending on whether you add liquidity or remove liquidity.
• A maker adds liquidity by placing a resting limit order that becomes part of the order book.
• A taker removes liquidity by hitting an existing quote, usually by crossing the bid ask spread.
The words describe your role in the execution, not your skill level.
Why this matters
Fees directly change your break-even probability. If you compute edge without correct fees, you will trade a lot of fake edge.
This is especially important in prediction markets where price ranges are bounded and small edges are common.
Maker behavior: you post, you wait
When you place a maker order, you try to get filled without paying the worst side of the spread:
• Instead of buying at the ask, you post a bid.
• Instead of selling at the bid, you post an ask.
Potential benefits:
• lower fees (depending on the platform)
• better price relative to immediate execution
• better expected value if you consistently avoid paying the spread
Taker behavior: you trade now
When you take, you prioritize immediacy. You remove liquidity and usually pay the spread:
• buy now means paying the ask
• sell now means hitting the bid
Potential benefits:
• certainty of execution
• faster entry when timing matters
• less chance your order sits unfilled while the market moves away
How maker taker fees change break even
Think in terms of all in price:
• executable price you actually get
• plus fees from the platform (fees)
That all in price is what drives break-even probability.
Simple approximation
If you buy YES at price p (0 to 1 scale), then ignoring everything else, your gross break even is about p. Once you add fees and spread costs, your effective break even moves upward.
Maker taker affects this because taker fees are often higher, and because takers more often cross the spread.
Worked example: maker vs taker on the same market
Assume a 0 to 100 price scale and the market shows:
• bid 49, ask 51
Taker entry
You buy now at 51 (implied probability 0.51). You also pay a taker fee.
Your break even might end up closer to 0.52 or 0.53 depending on the fee model and size.
Maker entry
You post a bid at 50 and get filled. You pay a maker fee that is lower (or sometimes zero).
Your break even might be closer to 0.50 to 0.51.
That is a meaningful difference. In small edge trading, 1 to 2 points is the whole trade.
But maker is not free money
Maker orders introduce execution risk. Your order may:
• not fill at all
• fill partially
• fill right before bad news hits (adverse selection)
That is why maker taker is not just a fee topic. It is also an execution risk topic.
When paying taker fees is rational
Taker is often correct when:
• timing matters and you cannot wait for a fill
• the book is thin and a posted maker order is unlikely to fill at your intended price
• you need to reduce risk quickly, for example to exit a position
• the market is moving and you prefer certainty over price improvement
How to measure the real impact
Two practical measurements help:
• Track your average fee per trade by order type (trading fee).
• Track execution relative to mid price using effective spread (fees added separately).
This separates market microstructure cost from platform fee cost, which is the clean way to improve.
What responsible platforms should surface
A platform that wants long term trust should make maker taker obvious:
• show fee estimates before order confirmation
• label whether your order is likely maker or taker
• show spread and depth so users understand why maker orders might not fill
That reduces user confusion and reduces churn from hidden costs.
Takeaway
Maker vs taker is not a small detail. It changes your all in price, which changes break even, which changes whether your edge is real. Prefer maker when you can wait and the book supports it. Prefer taker when timing or risk reduction matters. In both cases, compute break even using the fees and the executable side of the spread.
Related
• Fees vs Spread: The Two Costs Most Traders Mix Up
• Expected Value and Break-even Probability: Costs Turn Beliefs into Math
• Slippage, Price Impact, Execution Risk: Why Good Forecasts Still Lose Money