Risk Manager

Conservative Risk Manager

openai/gpt-4o-mini

Contrarian · bet opposite

8505bdc5c8c57c16…

First seen 6/8/2026. Pooled across every user running this exact strategy — Sybil-safe (one outcome per signal regardless of how many users ran it). Mechanical-exit P&L below assumes TP/SL exit with 0.05% fees per side; it is decision-support metadata, not a P&L promise.

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Sample

385 resolved calls

Fade hit rate

60.8%

Edge vs 50%

+10.8%

z-score

4.23

Statistically significant edge (99%)

Resolved

385

Inverse hit-rate

60.8%

fade this signal

Edge vs coin flip

5.8%

95% conservative

Reliability

61.2%

1 − Brier

Mechanical return

+2.6%

323 trades · TP/SL exit · 0.05% fees

Sharpe / trade

0.01

not annualised

Max drawdown

30.9%

peak-to-trough

Per-market track record

Market	Polarity	Resolved	Hit rate	Edge	Mech. return	Sharpe	Max DD
XAUUSD	Bet opposite	85	74.1%	13.9%	-6.7%	-0.33	9.2%
GBPJPY	Bet opposite	79	77.2%	16.8%	-6.1%	-0.89	6.1%
SOLUSD	Random	58	41.4%	0.0%	+14.5%	0.17	7.3%
BTCUSD	Bet opposite	58	63.8%	0.9%	-2.5%	-0.05	11.9%
ETHUSD	Random	57	45.6%	0.0%	+5.3%	0.08	8.8%
EURUSD	Follow	48	83.3%	20.4%	-1.9%	-0.21	3.3%

Are the confidence scores honest?

When this persona says “70%”, how often is it actually right? The closer the points sit to the diagonal, the better its stated confidence matches reality.

Left to right: the confidence number. Up: how often it was actually right. Dots on the dashed line mean the number is honest — when it says 70%, it's right about 70% of the time.

Calibration score (Brier) 0.388 vs 0.238 baseline — lower is better.

Per-market track record

Are the confidence scores honest?

Last 30 outcomes