Everything worth keeping on arbitrage detection in bot-driven trading: core mechanics, parameter choices, failure record.
How It Works
At the core of arbitrage detection sits a chain of transformations that turns raw market data into decisions an engine can act on.
Configuration
Configuring arbitrage detection comes down to a handful of parameters. Vendor defaults suit demos; production deserves its own tuning pass.
Failure Modes
The failure record for arbitrage detection includes regime changes, missed heartbeats, and positions that could not be closed gracefully.
Evaluation
Judge arbitrage detection on measured outcomes — distribution of returns, drawdown depth, operational burden — not on a single lucky stretch.
Configuration Reference
# Arbitrage Detection 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 |