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Erik
Erik

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How a Prediction Market Exchange Actually Works

#polymarket #trading #bot #tutorial

Prediction markets can look simple from the outside:

YES or NO?

But underneath, they work more like a financial exchange than a traditional betting platform.

If you're building a trading bot, understanding this infrastructure is essential.

1. A Market Represents an Event

Imagine a 5-minute BTC market:

Will BTC finish higher?

YES
NO
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Each outcome has a tradable position.

The price generally ranges between:

$0.00 → $1.00
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A YES price of $0.65 can roughly be interpreted as the market pricing a 65% chance of YES.

But the price isn't fixed by the platform.

It comes from buyers and sellers.

2. The Order Book

Prediction markets use an order book where traders submit bids and asks.

For example:

BIDS              ASKS

$0.48   500      $0.52   300
$0.47   800      $0.53   600
$0.46  1200      $0.54   900
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The highest bid is:

$0.48
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The lowest ask is:

$0.52
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The difference is the spread.

When a buyer accepts an available ask, the order can be matched.

3. Buying a YES Position

Suppose YES is trading at $0.60.

You buy:

100 YES
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Your cost is approximately:

100 × $0.60 = $60
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If YES wins:

100 × $1 = $100
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If YES loses:

$0
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You can also sell the position before the market resolves if another trader is willing to buy it.

That's why prediction markets can behave much more like trading markets than traditional bets.

4. What Happens to an Order?

A simplified order lifecycle looks like:

Create Order
     ↓
Sign Order
     ↓
Submit to Exchange
     ↓
Order Book
     ↓
Match
     ↓
Settlement
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In Polymarket's architecture, orders are matched through the CLOB while matched trades are settled onchain.

This creates a hybrid system:

Fast order matching
        +
Blockchain settlement
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For automated trading, this distinction is important.

5. Why Liquidity Matters

Imagine the order book contains:

$0.51 → 100 shares
$0.52 → 100 shares
$0.53 → 100 shares
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Buying 50 shares may be easy.

Buying 300 shares consumes multiple price levels.

Your average execution price can therefore become worse than the best ask.

This is slippage.

Instead of:

Buy 300 immediately
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a bot can execute:

100
 ↓
100
 ↓
100
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over time.

6. Resolution

Eventually, the event ends.

For example:

BTC finishes higher
        ↓
YES wins
        ↓
YES token → $1
NO token  → $0
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Winning positions can then be redeemed for their settlement value.

The complete lifecycle is:

Event
 ↓
YES / NO
 ↓
Order Book
 ↓
Trading
 ↓
Matching
 ↓
Settlement
 ↓
Resolution
 ↓
Redemption
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Why This Matters for Trading Bots

When building a prediction-market bot, the strategy is only one part of the system.

Your bot also needs to understand:

  • Order-book liquidity
  • Bid/ask spreads
  • Slippage
  • Partial fills
  • Order cancellation
  • Market resolution
  • Execution latency
  • Settlement

For example, a momentum strategy might say:

BTC momentum ↑
      ↓
Buy YES
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But the execution engine needs to answer:

Which price?
How much liquidity?
How much slippage?
Should I use TWAP?
Should I stop if momentum reverses?
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That's where prediction-market trading becomes an interesting engineering problem.

The signal tells you what to trade. The exchange determines how that trade actually happens.

Understanding the exchange is therefore the foundation for building better Polymarket trading bots.

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