How can you analyze short-term Bitcoin prediction markets using live BTC prices and Polymarket order book data?
This Polymarket trading bot in Python explores the relationship between three important signals: the external Bitcoin spot price, the TWAP-60s price reference, and the probability implied by Polymarket's live order book.
The goal is to identify potential pricing discrepancies and understand whether they represent meaningful trading opportunities.
Project links:
- 💻 GitHub:
Benj4minCup
/
Polymarket-Trading-Bot-python
polymarket trading bot polymarket twap bot polymarket arbitrage bot polymarket bot polymarket trading bot polymarket twap bot polymarket arbitrage bot polymarket bot polymarket trading bot polymarket twap bot polymarket arbitrage bot polymarket bot polymarket trading bot polymarket twap bot polymarket arbitrage bot polymarket bot polymarket trading
Polymarket Trading bot system
An open-source and Strong Strategy collection of Polymarket trading bot and Polymarket arbitrage bot and Polymarket TWAP trading bot in Python for high-performance automated trading on polymarket crypto 5min and 15min markets.
This repository is primarily intended for educational and research purposes. It includes strategy concepts, implementation approaches, and selected performance screenshots to help developers understand how different automated trading strategies can be designed and tested.
The repository does not provide a complete production-ready trading bot source code. Instead, it provides strategy descriptions and research materials that you can use as a foundation for developing your own system.
If you are interested in building a Polymarket Trading Bot, you can follow my tutorials and use the concepts in this repository to develop your own implementation.
For users who prefer a ready-to-deploy solution or require custom strategy development, commercial bot development and customization are also available.
Features
… - 🎥 YouTube demo:
- 📩 Telegram: https://telegram.me/BenjaminCup
What Is a Polymarket Trading Bot?
A Polymarket trading bot is a program that interacts with prediction markets to analyze prices, monitor market conditions, generate signals, or execute trades, depending on its implementation.
In Bitcoin prediction markets, traders may speculate on whether BTC will cross a price threshold or finish above or below a specified level.
The challenge is that the current Bitcoin spot price does not tell the whole story. The market's resolution rules, remaining time, liquidity, and order book prices also matter.
This project focuses on comparing those signals to better understand short-term BTC prediction markets.
1. Live Bitcoin Spot Price
The live BTC spot price represents Bitcoin's current trading price on an external cryptocurrency exchange.
A trading bot can use this price to monitor market movements and compare the underlying asset with Polymarket's current pricing.
For example, if BTC is trading at $100,050, that tells us where Bitcoin is trading on the selected exchange at that moment.
However, different exchanges can report slightly different prices due to liquidity and market conditions.
The external spot price is useful information, but it should not automatically be treated as the official resolution price for a Polymarket contract.
2. TWAP-60s: Understanding the Price Reference
TWAP stands for Time-Weighted Average Price.
A TWAP-60s calculation represents an average price over a 60-second window, based on the specific calculation method used.
Unlike a single spot-price observation, it incorporates price information over a period of time.
This can be important in short-duration Bitcoin prediction markets because BTC prices can move rapidly. The latest spot price and a time-averaged price may differ.
For example:
- Current BTC spot price: $100,050
- Example 60-second reference: $100,000
The difference between these values provides context for analyzing the market.
Important: Always verify the resolution rules for the specific Polymarket contract. Do not assume that a TWAP-60s value is the official settlement reference unless the market rules specify it.
3. Polymarket Order Book and Implied Probability
The Polymarket order book displays bids and asks for outcome tokens.
For example, imagine a hypothetical YES market with the following prices:
| Order book metric | Example |
|---|---|
| Best YES bid | $0.56 |
| Best YES ask | $0.60 |
| Midpoint | $0.58 |
| Indicative midpoint probability | 58% |
A YES token priced at $0.58 can be interpreted as an indicative 58% market-implied probability, assuming the token pays $1 if YES resolves successfully and $0 otherwise.
However, the midpoint is not necessarily an executable trading price.
A buyer seeking immediate execution generally needs to consider the ask price, available liquidity, fees, and slippage.
The order book reflects traders' expectations, market liquidity, uncertainty, and the time remaining until resolution.
These figures are illustrative examples, not live Polymarket prices.
4. How the Polymarket BTC Trading Bot Works
The analysis process follows a simple workflow.
- Retrieve the external BTC spot price.
- Calculate or retrieve the relevant TWAP-60s value.
- Read the current Polymarket order book.
- Compare the price data with the contract's threshold and resolution rules.
- Examine the market-implied probability.
- Evaluate potential discrepancies, liquidity, and execution costs.
The important idea is to compare the underlying Bitcoin market with the price of the prediction market outcome.
A difference between the signals may justify further investigation, but it does not automatically indicate a profitable trade.
5. Why Can BTC Prices and Polymarket Probabilities Differ?
Several factors can explain apparent discrepancies.
Different price sources
The BTC price on an external exchange may not match the price source used to resolve the Polymarket contract.
Market update delays
Bitcoin can move quickly, while prediction-market quotes may update at a different pace.
Time until resolution
If BTC is currently above a threshold, the probability of finishing above it still depends on how much time remains and how volatile the market is.
Order book liquidity
A displayed price may be available for only a small number of tokens. Larger orders can receive worse execution prices.
Trading costs
Fees, bid-ask spreads, slippage, and latency can eliminate an apparent pricing advantage.
A useful Polymarket trading strategy must consider these factors rather than relying on a simple comparison between two prices.
6. Why Order Book Analysis Matters
Consider a YES token with a bid of $0.56 and an ask of $0.60.
The four-cent spread represents the difference between the best displayed buying and selling prices.
If a bot calculates probability using only the midpoint, it may overlook the cost of entering or exiting a position.
A more realistic analysis considers:
- Best bid and ask.
- Available liquidity at each price level.
- Expected execution price for the intended order size.
- Trading fees and slippage.
- Data freshness and timing.
- The contract's actual resolution conditions.
These checks help distinguish a theoretical pricing discrepancy from a potentially executable opportunity.
7. Explore the Python Polymarket Trading Bot
You can inspect the project source code and watch the demonstration using the links below.
GitHub repository
Polymarket Trading Bot — Python
Explore the source code, project structure, and implementation:
https://github.com/Benj4minCup/Polymarket-Trading-Bot-python
YouTube demo
Watch the project demonstration:
https://www.youtube.com/watch?v=UCF7MA1Kekk
Connect on Telegram
Have questions or want to discuss prediction markets, Python automation, or trading-bot development?
https://telegram.me/BenjaminCup
Conclusion
A Polymarket trading bot can analyze more than the current Bitcoin price.
Comparing the external BTC spot price, a TWAP-60s reference, and the live Polymarket order book provides a framework for studying short-term prediction markets.
Each signal serves a different purpose:
- BTC spot price: Shows where Bitcoin is trading now.
- TWAP-60s: Represents price behavior across a selected time window.
- Order book: Shows the prices traders currently offer for prediction-market outcomes.
The main challenge is determining whether an apparent probability discrepancy remains meaningful after accounting for resolution rules, time to expiry, liquidity, and trading costs.
If you are interested in building a Polymarket trading bot with Python, exploring order book data, or studying Bitcoin prediction markets, check out the repository and demo above.
Disclaimer: This project is presented for educational and research purposes. Trading involves risk, and no strategy guarantees profit.
