feat: capital-temperature position sizing (shadow-default) - #12
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Consume the composite capital_temperature (0..1) that context-service already publishes in market:context and use it to auto-scale BUY position size — the "is this a good environment to be a buyer at all?" gap. Nothing consumed that signal before; the risk-engine had a weaker VIX+HY-only temperature whose size reduction decision-engine discarded. - market_context: parse capital_temperature.value (clamped 0..1; absent → 0.0 = no reduction) + get_capital_temperature(). - service: _apply_capital_temperature folds temp into the tier size multiplier — temp_mult = 1 - temp*max_reduction (default 0.50), combined = tier*temp_mult, re-clamped to 2% by the existing trade-planner seam. ALWAYS logs the would-be effect; only APPLIES when capital_temperature_sizing_enabled=True. - config: capital_temperature_sizing_enabled (default False = shadow) + capital_temperature_max_reduction (0.50), mirroring feedback_accuracy_enabled. Scales SIZE (complementing the regime multiplier which scales CONFIDENCE). Ships shadow-default: logs what it would do against live signals, applies nothing until the flag flips. +12 tests; suite 880 green. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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What
Lights up the Composite Risk / Capital-Temperature Score (gap-analysis Phase B, Gap 3): auto-scale BUY position size by the composite
capital_temperature(0..1, 0=risk-on … 1=stressed) that context-service already publishes inmarket:context. This is the "don't buy into weakness" brake that was missing when MOH was bought.Why now / what was missing
The weighted composite gauge already exists in context-service — but nothing consumed it. decision-engine read only
regime/regime_confidence. A separate, weaker VIX+HY-only temperature in risk-engine computed a size reduction that decision-engine discarded (it uses risk-engine only as a pass/fail gate). So the real production sizer never saw temperature at all.Changes (decision-engine only)
market_context.py— parsecapital_temperature.value(clamped 0..1; absent/malformed → 0.0 = no reduction) +get_capital_temperature().service.py—_apply_capital_temperaturefolds temp into the tier size multiplier at the existing seam:temp_mult = 1 − temp×max_reduction(default 0.50 → full stress halves size),combined = tier × temp_mult, re-clamped to 2% by the trade planner. Always logs the would-be effect; only applies when the flag is on.config.py—capital_temperature_sizing_enabled(default False = shadow) +capital_temperature_max_reduction(0.50), mirroringfeedback_accuracy_enabled.Scales size (complementing the regime multiplier, which scales confidence — two distinct levers, deliberately not mixed).
Rollout
Ships shadow-default: against live signals it logs e.g.
capital-temperature sizing AAPL: temp=0.64 → ×0.68 (tier ×1.15 → combined ×0.78) [shadow], applying nothing untilCAPITAL_TEMPERATURE_SIZING_ENABLED=true. Real-time observability during shadow, same as the hard gate.+12 tests (parsing/clamp/absent, shadow-vs-enabled, tier combination, max_reduction, no-reader). Full suite 880 green.
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