Prediction markets have become one of the most interesting places to build trading algorithms. Unlike traditional exchanges, markets on Polymarket are driven by probabilities, news, and trader behavior, creating unique opportunities for quantitative analysis.
Over the past few weeks, I've been building a Polymarket wallet analyzer that helps me understand how profitable traders actually operate. Instead of blindly copy trading successful wallets, the goal is to reverse engineer their strategies and eventually build an intelligent trading bot.
🎥 Demo Video
Watch the full walkthrough of the wallet analyzer and trading bot below:
In the video I demonstrate:
- Wallet performance analysis
- Market-by-market statistics
- YES vs NO trading behavior
- Trade history expansion
- P&L visualization
- Wallet classification
- Future trading bot roadmap
🚀 Open Source Repository
The entire project is open source.
GitHub Repository:
nahuelvivas
/
Polymarket-Arbitrage-Trading-Bot
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Polymarket Arbitrage Trading Bot
This Polymarket arbitrage trading bot is designed for high-frequency execution during the final seconds of each 5-minute BTC and ETH prediction market epoch. The bot continuously monitors price differences between Chainlink oracle pricing and Polymarket market prices to identify short-term arbitrage and trading opportunities.
Rather than relying on a single market signal, the bot requires confirmation from both BTC and ETH before opening a position. This dual-market confirmation helps reduce false signals and improves trade quality during highly volatile market conditions.
Before executing a trade, the bot evaluates several risk filters, including market liquidity, bid-ask spread, repeated price confirmation, and execution conditions. When all requirements are satisfied, the bot automatically enters either a YES or NO position with low-latency execution.
The strategy focuses on rapid trade management instead of holding positions. After entry, the bot exits quickly using strict risk controls such as time-based exits, volatility…
Feel free to:
- ⭐ Star the repository
- Fork it
- Open issues
- Submit pull requests
- Build your own trading strategies
Community contributions are always welcome.
The Problem with Copy Trading
Most people see a profitable wallet and immediately start copying every trade.
The problem is that profitability alone doesn't tell you why a trader is winning.
Questions that matter include:
- Are they market making?
- Are they trading momentum?
- Do they hedge both YES and NO positions?
- How long do they hold trades?
- Do they react to volatility?
- Are they following external markets like Binance?
- Are they simply getting lucky?
Without answering these questions, copy trading becomes gambling.
Building a Wallet Analyzer
To solve this problem, I started building an analytics dashboard that breaks down every wallet into measurable statistics.
Instead of looking at a balance, I want to understand the trader's behavior.
Some of the metrics include:
- Total P&L
- Win rate
- Number of trades
- Average position size
- Average return per trade
- Trading frequency
- Markets traded
- YES vs NO distribution
- Hourly activity
- Daily activity
- Position duration
These metrics help classify different trading styles.
For example, one wallet may execute hundreds of trades every day with tiny profits, while another only trades a few high-conviction events.
Market-Level Analysis
One feature I found particularly useful is analyzing performance per market.
Instead of looking at a trader's overall profit, I can inspect individual prediction markets and see:
- Number of trades
- Profit percentage
- YES orders
- NO orders
- Buy/sell ratio
- Filled positions
- Exposure
Sometimes a trader executes over 300 trades in a single market while maintaining an impressive return.
Seeing this information makes it much easier to understand whether someone is consistently profitable or simply had one lucky trade.
Understanding Both Sides of the Market
One interesting pattern is that many profitable traders don't only buy YES.
They actively trade both sides.
In many markets they:
- Buy YES
- Buy NO
- Rebalance positions
- Capture price movement
- Reduce directional risk
This looks much closer to market making than traditional betting.
Understanding this behavior is one of the main goals before attempting to automate any strategy.
Zooming Into Individual Trades
Another feature I'm building allows expanding every trade inside a market.
Instead of seeing summary statistics, I can inspect the entire trading history.
This raises interesting questions:
- When does the trader enter?
- When do they exit?
- Do they scale into positions?
- Do they average down?
- Do they hedge?
- Do they wait for volatility?
- Do they respond to external exchanges like Binance?
Answering these questions is far more valuable than simply copying positions.
Not Every Profitable Wallet Is Worth Copying
One surprising discovery is that some wallets with relatively low win rates still generate impressive profits.
How?
Because their winners are significantly larger than their losers.
For example, a trader might lose many small positions but make substantial gains from a few large winning trades.
Looking only at win rate would completely miss this pattern.
Position Size Matters
Another important metric is average trade size.
Some profitable traders consistently buy contracts around one cent.
While many of these trades expire worthless, the occasional winning position generates enormous returns.
This is a very different strategy from traders who buy contracts already priced at 70–90%.
Understanding risk management is just as important as understanding profitability.
Finding Wallets Automatically
One challenge with manual analysis is discovering new wallets.
Currently, many traders simply share profitable wallets on social media, causing thousands of people to copy them.
Eventually those wallets often stop trading or change behavior.
To solve this, I'm building an automatic wallet discovery system.
Instead of relying on viral posts, the application will continuously scan for wallets that meet specific performance criteria.
This allows traders to discover promising strategies before they become widely known.
The Bigger Goal: Building a Trading Bot
The wallet analyzer is only the first step.
The long-term objective is building a Polymarket trading bot that learns from historical trading behavior rather than blindly copying wallets.
The workflow looks something like this:
- Discover profitable wallets.
- Analyze historical performance.
- Classify trading strategies.
- Detect recurring trading patterns.
- Build models that recognize similar opportunities.
- Execute trades automatically.
Rather than imitating a single trader, the bot will learn from many successful traders and identify common characteristics.
Improving the User Experience
Alongside the analytics engine, I've also been improving the application's interface.
The dashboard now provides:
- Better wallet summaries
- Cleaner market statistics
- Interactive trade expansion
- Performance charts
- Position breakdowns
- Easier navigation between wallets
The goal is making it simple to explore thousands of trades without feeling overwhelmed.
What's Next?
I'm currently finishing the frontend and polishing the wallet analysis engine.
The next major update will introduce automatic wallet discovery, making it easier to identify high-quality traders for further research.
The application will be available for free, allowing anyone interested in prediction markets to study successful trading strategies without needing expensive subscriptions.
This project isn't about blindly copying wallets.
It's about understanding why certain traders consistently outperform the market—and using that knowledge to build smarter, data-driven trading systems.
📺 Follow the Development Journey
I'll be sharing future updates, new features, wallet discoveries, and trading bot improvements on YouTube.
YouTube Channel
youtube.com
If you're interested in Polymarket, algorithmic trading, blockchain analytics, or building trading tools, consider subscribing to follow the project's progress.
Thanks for reading, and happy building! 🚀
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