Everything worth keeping on sensitivity analysis in bot-driven trading: core mechanics, parameter choices, failure record.
How It Works
At the core of sensitivity analysis sits a chain of transformations that turns raw market data into decisions an engine can act on.
Configuration
Configuring sensitivity analysis comes down to a handful of parameters. Vendor defaults suit demos; production deserves its own tuning pass.
Failure Modes
Documenting how sensitivity analysis fails teaches more than documenting how it succeeds. Regime shifts, infrastructure faults, and drift top the list.
Evaluation
Judge sensitivity analysis on measured outcomes — distribution of returns, drawdown depth, operational burden — not on a single lucky stretch.
Configuration Reference
# Sensitivity Analysis 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 |