> ## Documentation Index > Fetch the complete documentation index at: https://docs.into.space/llms.txt > Use this file to discover all available pages before exploring further. # Overview > What you can build on Space Dev1 Pn Space provides the infrastructure for prediction markets. Here are some examples of what developers will be able to build on top with data pushed and pulled from our platform. ## Trading Tools **Automated Bots**\ Monitor probability movements and execute strategies. Buy when the market underprices an outcome, sell when it corrects. Space's [0% maker fees](/concepts/makers-takers) and [transparent order book](/architecture/clob) make algorithmic trading viable. *Example strategy:* Mean reversion bot that buys YES shares when probability drops below historical average and sells when it rises above threshold. **Arbitrage Scanners**\ Compare Space prices to Polymarket, Kalshi, or traditional trading markets. Execute when spreads exceed transaction fees.\ [Multi-outcome markets](/architecture/multi-outcome) create additional arbitrage opportunities - if NO shares for one outcome are mispriced relative to YES shares for another, convert and capture the spread. **Portfolio Managers**\ Track positions across multiple markets, calculate total PnL, manage risk exposure. With [leverage](/architecture/leverage) available, capital efficiency matters. Portfolio tools help users optimize allocation and monitor liquidation risk. **Alert Systems**\ Notify users when: * Probability hits specific threshold * Large trades execute (whale watching) * Market approaching resolution * Liquidation risk increases Real-time [WebSocket feeds](/api/websocket) make this straightforward. Push notifications via email, SMS, Discord, or Telegram. ## Analytics Platforms **Market Dashboards**\ Visualize trends, volume, and liquidity across markets. Answer questions like: * Which outcomes are moving? * Where is capital flowing? * What do traders believe? * How has sentiment changed over time? Build charts showing probability evolution, volume heatmaps, and trader activity patterns. **Trader Leaderboards**\ Track top performers across markets. Show: * Total ROI over time periods * Win rate on resolved markets * Average position size * Risk-adjusted returns Prediction markets reward accuracy. Make reputation visible and trackable. **Historical Analysis**\ Backtest trading strategies against historical market data. Study: * Market behavior at different time horizons * When probabilities stabilize before resolution * Correlation between market movements and news events * Accuracy of prediction markets vs. other forecasting methods **Whale Watching**\ Monitor large trades that significantly move markets. Alert when conviction trades happen. In thin markets, size matters - track who’s making bold predictions and how often they’re right. ## Data Services **Price Feeds**\ Aggregate Space probabilities for external use. Potential applications: * DeFi protocols using prediction market odds as oracle inputs * Research firms studying market sentiment * News organizations tracking real-time sentiment on events * Traditional finance firms incorporating prediction data **News Integration**\ Correlate market movements with breaking news: * When did the market react to an announcement? * How fast did probabilities update after news broke? * What information moved the odds the most? * Which news sources have the strongest impact? Build tools that overlay news timelines on price charts, identify market-moving events, and track information propagation speed. **Sentiment Analysis**\ Compare prediction market probabilities to: * Social media sentiment (Twitter, Reddit) * Traditional polling data * Expert forecasts * Trading market odds Identify where the market disagrees with conventional wisdom. These divergences often signal valuable information or mispricing. ## DeFi Integrations **Collateral Protocols**\ Use shares as collateral for loans. YES shares trading at \$0.80 have predictable value - lend against them. Create lending pools where users can borrow USDC against their prediction market positions. **Yield Strategies**\ Automated liquidity provision: * Place limit orders on both sides of order book * Capture bid-ask spread as profit * Rebalance as market moves * Optimize for markets with highest volume/spread ratio Earn yield by providing depth to markets while maintaining market-neutral exposure. **Derivatives**\ Build options or structured products on prediction markets: * Call/put options on market probabilities * Range-bound products (profit if probability stays within range) * Volatility products (profit from probability swings) Space provides the base layer. Derivatives add leverage and new risk/reward profiles. ## Example: Trading Bot Flow A bot monitoring BTC price markets: Fetch current probability via [REST API](/api/rest).\ Subscribe to trades via [WebSocket](/api/websocket) for real-time updates. Compare current probability to historical average.\ Check if below entry threshold (e.g., 30%).\ Calculate position size based on conviction and risk limits. Place limit order slightly below current price.\ Pay 0% fee as maker.\ Monitor for fill via WebSocket. Track unrealized PnL as probability changes.\ Set exit target (e.g., sell when probability reaches 50%).\ Implement stop-loss if needed. Place limit sell order when target hit.\ Or use market order for immediate exit (pays dynamic fee).\ Calculate realized PnL. Track performance across trades.\ Adjust strategy based on results. All of this is possible with Space's [transparent order book](/architecture/clob), real-time data feeds, and 0% maker fees.