Markets move faster than deploy pipelines. Your bot is live, volatility spikes, and you need to cut position size, tighten stop-loss, or halt new entries — now, not after the next release.
Kiponos.io gives Python trading systems live risk parameters: in-memory reads in the execution loop, WebSocket deltas from ops or a risk supervisor.
The execution-loop rule
def should_enter(kiponos, signal):
risk = kiponos.path("risk", "intraday")
if risk.get_bool("halt_new_entries"):
return False
if portfolio.drawdown() > risk.get_float("max_drawdown_pct"):
return False
return signal.strength > risk.get_float("min_signal_strength")
Every get_* is a local read — no HTTP between your bot and the exchange path.
Risk config tree
risk/
intraday/
max_position_usd: 25000
max_drawdown_pct: 3.5
stop_loss_pct: 1.2
halt_new_entries: false
min_signal_strength: 0.65
symbols/
BTC/
max_position_usd: 10000
ETH/
max_position_usd: 8000
Supervisor + operator control
| Actor | Action |
|---|---|
| Risk analyst | Lower max_position_usd in dashboard during news event |
| Supervisor algo | Set halt_new_entries: true when VaR exceeds limit |
| Trader | Per-symbol caps without restarting bot process |
Same pattern as live ML hyperparameter tuning: writers update Kiponos, readers stay in the hot loop.
Performance
- WebSocket background thread applies deltas
- Bot thread only touches cached values
- Changing one float does not reload full config tree
Start at kiponos.io. Resources: github.com/kiponos-io/kiponos-io
Kiponos.io — real-time config for Python. Adjust risk while the market is open.
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