research: prepare effective risk floor ab
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# Effective initial-risk floor A/B - frozen specification
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Date frozen: 2026-08-05
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Branch: research/portfolio-capacity-rebalancing
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Runner: scripts/run_portfolio_construction_matrix.py
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Study ID: risk-floor-ab
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## Question
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Does rejecting an otherwise qualified cap-10 entry when its actual initial
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stop-risk after cash and notional sizing is below 0.5% of marked equity improve
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trade selection?
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The completed capacity bracket cannot answer this. Its cash_unbounded arm
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removed the count cap and applied the 0.5% floor simultaneously. In the 70 paths
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where the control cap never bound, that arm still raised mean EV from 0.328 to
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0.399 R and profit factor from 1.60 to 1.75 while trades fell about 8% and
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exposure stayed nearly flat. Capacity was a no-op in those paths, so the floor
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is the plausible cause, but the prior arm remains confounded.
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This A/B changes only the floor. It has no formal promotion gate and does not
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automatically change production.
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## Frozen arms
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1. cap10_incumbent: current production-style cap-10 control, with no minimum
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effective-risk floor.
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2. cap10_min_risk_005: the same cap-10 strategy, rejecting an entry only when
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actual initial stop-risk after cash/notional sizing is below 0.5% of marked
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equity.
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Both arms have max_positions=10, weekly replacement disabled, 1% target risk
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per trade, and identical admission ordering. The only differing simulator
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argument is min_initial_risk_fraction: None versus 0.005.
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All other settings remain the frozen daily Phase A control: current production
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construction universe, full-universe residual-momentum/low-volatility 80/20
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rank, threshold 80, normal gate-reset re-entry, close fills, 3x ATR trail,
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30-session maximum hold, 20% per-position notional ceiling, no leverage, and
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costs of 0.10% and 0.20% per fill.
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Every priced symbol contributes to the daily cross-sectional rank. Rank-only
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symbols cannot submit trades. Validation retains the 450-600-symbol production
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construction guardrail and the legacy-snapshot column-scoped loader.
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## Frozen cohorts
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Reuse the completed bracket's point-in-time daily candidate/rank cache and
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cohort manifest:
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- Empty book: first eligible session of each month in 2019-2025, with 504 prior
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scoring sessions and 252 measurement sessions. This is the primary start-date
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evidence.
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- Warm book: weekly seeds 63-126 sessions before each 2019-2025 annual anchor,
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with state carried into the same 252-session measurement window. This is a
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state-carrying replication, not independent evidence.
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The expected realization is 78 empty-book paths, 97 warm paths, seven annual
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clusters in each protocol, two costs, two arms, and 700 cells.
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Do not use warm-seed IQR as evidence. Six of seven completed-bracket anchors
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were structurally degenerate because fractional sizing is scale invariant and
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the 30-session maximum hold washed out books before anchors. The 2023 exception
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shows that state carrying itself works.
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## Reporting and interpretation
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For every protocol and cost, pair identical paths. Report:
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- mean, median, P25, and P75 paired net-EV changes in R;
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- positive-path and bit-identical-path fractions;
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- the median paired delta within each year and the median across seven years;
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- simple 90% cluster-bootstrap context for EV and Calmar, with no CI gate;
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- mean paired PF, Gain-to-Pain, Sortino, Calmar/MAR, CAGR, maximum drawdown,
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total return, and Sharpe changes;
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- trades, floor rejections, holding time, cash, gross exposure, average/peak
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positions, turnover, and costs.
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Means and identical-path fractions must appear beside medians so inert cohorts
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cannot turn a left- or right-skewed treatment into a misleading zero headline.
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For these 252-session windows, the implementation's full-window Calmar is CAGR
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divided by maximum drawdown, the same numeric definition commonly called MAR;
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do not present the duplicate label as a second independent metric.
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Today's production membership is projected backward. Use paired differences
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for the treatment conclusion; absolute profitability remains descriptive and
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survivorship-biased. Empty and warm protocols cover the same seven market years
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and must not be interpreted as independent replications.
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Interpretation is deliberately simple:
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- a positive result means the isolated floor improves the paired EV
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distribution without an economically important loss of total-return or
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drawdown quality;
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- a negative result closes the floor;
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- mixed EV/portfolio-quality results are reported as a trade-off, not forced
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through a composite score.
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## Reproducibility and macOS execution
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The authoritative run refuses a dirty worktree. Its fingerprint includes the
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implementation commit, this specification hash, snapshot hash, candidate-cache
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key, construction view, cohort manifest, arm definitions, costs, and study
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version. Cells checkpoint atomically and --resume verifies the fingerprint.
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From the repository root on macOS:
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python3 -m venv .venv
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./.venv/bin/python -m pip install -e '.[dev]'
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Preflight, reusing the completed bracket's candidate/rank cache:
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./.venv/bin/python scripts/run_portfolio_construction_matrix.py + backtest_snapshots/research.sqlite + --study risk-floor-ab + --run-id prod505-effective-risk-floor-ab-daily-v1 + --candidate-cache reports/.cache/prod505-capacity-bracket-daily-v1-candidates.pkl + --workers 8 + --resume + --validate-only
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Authoritative run:
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./.venv/bin/python scripts/run_portfolio_construction_matrix.py + backtest_snapshots/research.sqlite + --study risk-floor-ab + --run-id prod505-effective-risk-floor-ab-daily-v1 + --candidate-cache reports/.cache/prod505-capacity-bracket-daily-v1-candidates.pkl + --workers 8 + --resume
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On an M2 Pro, eight workers is the explicit high-utilization setting. Use six
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instead on a memory-constrained machine; auto intentionally caps itself at six.
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Changing worker count does not change the fingerprint or results.
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Commit only the compact final JSON and Markdown reports. Candidate caches,
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checkpoints, raw curves, and trade ledgers remain ignored.
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