A mapped reference for prediction market bots — how it runs, how to configure it, and where it runs aground under load.
Mechanics
The mechanics of prediction market bots form one pipeline: raw market data in, computed signal out, decision routed to the order engine.
Waypoints (Configuration)
Configuring prediction market bots comes down to a short list of parameters. Vendor defaults fit demonstrations; live deployment deserves its own pass.
Wreck Record (Failure Modes)
The wreck record for prediction market bots teaches more than the success story. Regime shifts, infrastructure faults, and drift lead the list.
Navigation Checks (Evaluation)
Evaluate prediction market bots on measured outcomes — return distribution, drawdown depth, operational burden — never on one lucky stretch.
Configuration Reference
# Prediction Market Bots tested configuration mode: production timeframe: auto risk_limits: max_drawdown: 15 percent max_position: 3 percent monitoring: alert_threshold: 0.5 report_interval: hourly
Parameter Impact
| Parameter | Effect | Trade-off |
|---|---|---|
| timeframe | Signal frequency | Higher means fewer but more reliable signals |
| risk_limit | Maximum exposure | Lower means safer but slower returns |
| lookback | Indicator sensitivity | Longer means smoother but lagging |