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Benjamin-Cup

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Building a High-Probability Trading Bot for Polymarket’s 5-Minute BTC Market

Introduction

Prediction markets like Polymarket offer a unique structure where pricing is not purely driven by traditional order books, but by probabilistic expectations tied to real-world (or oracle-based) outcomes. In the 5-minute BTC market, token prices reflect the likelihood that the final settlement price will meet a predefined target.

Through observation and experimentation, I identified a consistent relationship between three variables:

  • Time remaining until market resolution
  • Price difference between the target and the current BTC price
  • Token price (market-implied probability)

This insight enabled the development of a trading bot that exploits predictable inefficiencies in short timeframes.


Core Observation

The key pattern is simple:

When the remaining time is short and the price difference is sufficiently large, the token price tends to approach certainty (close to 1 or 0).

Some empirical examples:

  • 110 seconds remaining + difference > 90 → token price > 0.9
  • 150 seconds remaining + difference > 150 → token price > 0.9
  • 80 seconds remaining + difference > 70 → token price > 0.9

This suggests a dynamic threshold:

The required price difference scales roughly with time remaining.

In other words, the market becomes increasingly confident as:

  • Time decreases
  • Price deviation becomes harder to reverse

Strategy Design

1. Defining the “Field”

I defined a “field” as a condition where:

difference ≥ f(time_remaining)
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and the corresponding token price is expected to exceed a high probability threshold (e.g., 0.9).

This field represents a zone where the market is very likely to resolve in a specific direction.


2. Position Splitting

Instead of entering a single large position, the bot:

  • Splits capital into multiple smaller tokens
  • Enters positions incrementally
  • Maintains flexibility for exit timing

This reduces risk and improves execution efficiency.


3. Execution Logic

Once inside the defined field:

  1. Monitor market continuously
  2. Sell lower-priced tokens first
  • Locks in early profit
  • Reduces exposure

    1. Sell higher-priced tokens later
  • Captures maximum value as probability converges toward 1

This staggered exit approach balances:

  • Profit realization
  • Risk control
  • Market liquidity

Why This Works

This strategy works due to structural inefficiencies:

1. Latency in Market Adjustment

The token price does not instantly reflect changes in probability, especially in fast-moving, short-duration markets.

2. Behavioral Bias

Traders may:

  • Overestimate reversals
  • Hesitate to price in near-certainty too early

3. Deterministic Constraints

With limited time, large price reversals become statistically unlikely, yet markets may not fully price this in immediately.


Performance

Using this approach:

  • Win rate: Over 99%
  • Consistency: High, due to rule-based execution
  • Risk profile: Controlled via position splitting and early exits

However, it’s important to note:

A high win rate does not eliminate tail risk.

Rare but extreme BTC movements can still invalidate assumptions.


Result Screenshot


Risk Considerations

No strategy is risk-free. Key risks include:

  • Sudden BTC volatility (sharp reversals)
  • Oracle delays or discrepancies
  • Liquidity constraints when exiting positions
  • Model overfitting to historical conditions

Mitigation strategies:

  • Conservative thresholds
  • Dynamic adjustment of the “field”
  • Strict position sizing

Future Improvements

Potential enhancements include:

  • Adaptive threshold modeling using historical volatility
  • Machine learning for dynamic probability estimation
  • Multi-market arbitrage across different durations
  • Real-time volatility weighting

Conclusion

By identifying a consistent relationship between time, price difference, and probability, it’s possible to build a highly effective trading strategy in Polymarket’s 5-minute BTC markets.

The key insight is simple but powerful:

As time runs out, probability converges faster than the market often prices in.

Exploiting that gap—systematically and with discipline—creates a durable edge.


🤝 Collaboration & Contact

If you’re interested in building trading bots, buy trading bots, collaborating, exploring strategy improvements, or discussing about this system, feel free to reach out.

I’m especially open to connecting with:

Quant traders
Engineers building trading infrastructure
Researchers in prediction markets
Investors interested in market inefficiencies

📌 GitHub Repository

This repo has some Polymarket several bots in this system.
You can explore the full implementation, strategy logic, and ongoing updates about 5 min crypto market here:

GitHub logo Bolymarket / Polymarket-arbitrage-trading-bot-python

polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage trading bot polymarket V2 arbitrage

Polymarket Arbitrage Trading Bot | V2 Ready

Polymarket Trading Bot • 5-Min Market Bot • Fully Automated System

A high-performance, automated trading system for Polymarket prediction markets — now fully upgraded for Polymarket V2.

Built in Python, the system leverages real-time WebSocket data, gasless L2 execution, and an advanced risk-management framework optimized for short-term and high-frequency trading environments.

🚀 V2 Upgrade Highlights

  • Full compatibility with the new V2 exchange architecture
  • Updated SDK/API integration
  • Support for new order structures & contract addresses
  • Integrated pUSD collateral flow (via USDC.e wrapping)
  • Improved execution reliability during high-volatility windows
  • Seamless handling of order cancellations and migration events

Designed for arbitrage, directional strategies, and ultra-short-term markets (including 5-minute rounds), this bot framework provides a robust foundation for building and scaling automated trading strategies on Polymarket V2.

image

Contact

I have extensive experience developing automated trading bots for Polymarket and have built several profitable bots. and updating all…




💬 Get in Touch

If you have ideas, questions, or would like to collaborate or want these trading bots, don’t hesitate to reach out directly.

Feedback on your repo (based on your description & strategy)

Contact Info

Email
benjamin.bigdev@gmail.com

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