P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT · P(TP < SL | xₜ, regime) · E[R] = p·2.5R − (1−p)·1R · if evidence < threshold: WAIT ·
feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision · feed → freshness → normalize → features → regime → score → risk → decision ·
zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only · zₜ = (xₜ − μₜ) / σₜ · spread + slippage + latency · closed candles only ·
P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward · P(y=1|x) ≠ certainty · drawdown(t) = peak − equity(t) · risk before reward ·
setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger · setup ∈ {qualified, rejected, wait} · outcome → calibration → challenger ·
How does it think?
Evidence enters. Weak setups die. Risk gets the final word.
Market feed → freshness → normalization → features → regime → scoring → risk → decision.
Every stage can reject the setup. WAIT is not an error; it is a decision.
Less prediction theatre. More measured uncertainty.
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