diff --git a/.gitignore b/.gitignore index ed43583..2d776d9 100644 --- a/.gitignore +++ b/.gitignore @@ -43,3 +43,6 @@ combined-ca-bundle.pem # Backtest reports in reports/ are tracked: they are the evidence behind the # production baseline in the README. The snapshot DBs they run against are not. backtest_snapshots/ +# Rebuildable pickle caches are local accelerators, not decision evidence. +reports/*.pkl +reports/*.pk1 diff --git a/README.md b/README.md index a0032d3..397a365 100644 --- a/README.md +++ b/README.md @@ -60,6 +60,8 @@ flowchart TD **What happens after an initial stop.** The stop always closes the trade and realizes its costs. The ticker is then locked until a successful daily full-universe scan first observes it outside the production gate and a later scan observes a fresh qualification. A continuously qualified ticker therefore cannot generate an immediate duplicate entry. Other exit reasons do not start this reset. See the [daily post-stop re-entry study](docs/research/post-stop-reentry.md). +**Live timing matters.** The full daily pipeline runs the R:R scan before Outcome Eval. A stop closed by that Outcome Eval—or by an intraday evaluation after the day's full scan—therefore cannot use its stop-day gate state. The earliest failure observation is the next successful full scan, and requalification needs a subsequent full scan. The research `gate_reset` arm evaluated the stop before its same-session gate check; the live boundary is consequently analogous to the study's stricter `strict_gate_reset` arm. This known event-ordering difference is quantified below. + ## How It Works Scheduled pipelines turn raw prices into a ranked, gated list of tradeable setups. Everything downstream of OHLCV is recomputed from stored data, so each refresh is cheap and idempotent. Job timing is cron-based and configurable in **Admin → Jobs** (default timezone Europe/Berlin). @@ -185,11 +187,14 @@ The production policy is **normal gate reset**, evaluated with daily setup oppor | Re-entry policy | Total return | CAGR | Max DD | Sharpe | Trades | |---|---:|---:|---:|---:|---:| | Immediate | 348.4% | 45.2% | -24.3% | 1.67 | 489 | -| **Gate reset (production)** | **388.1%** | **48.3%** | **-21.6%** | **1.77** | **472** | +| **Gate reset (selected study arm)** | **388.1%** | **48.3%** | **-21.6%** | **1.77** | **472** | +| Strict gate reset (live timing analogue) | 342.7% | 44.8% | -23.4% | 1.68 | 471 | | Fixed five-session cooldown | 250.8% | 36.6% | -22.2% | 1.47 | 473 | In the disjoint 2025+ book, gate reset also beat immediate re-entry (Sharpe 1.66 vs 1.55; CAGR 41.8% vs 39.3%) and the fixed five-session rule (Sharpe 1.43; CAGR 32.7%). Its lead over both survived costs of 0.2% and 0.3% per side. The result is capacity-specific: cooldown 5 won at capacity 5, while immediate had slightly higher return and Sharpe at capacity 15. Production uses capacity 10, so that is the portfolio for which this decision is valid. +Those promotion numbers belong to the selected normal-reset study arm. Under the live scheduler's stricter first-observation timing, the full-period analogue was Sharpe 1.68 / CAGR 44.8% / DD 23.4%; in the disjoint 2025+ book it was Sharpe 1.38 / CAGR 32.9% / DD 21.0%. The matrix therefore validates the state-machine choice but is not exact scheduler-order parity. Closing this timing gap would require a separately reviewed pipeline-order change, not a documentation reinterpretation. + `gate_reset` and a simple `next_session` block happened to produce the same executed live-universe portfolio in this sample. Their rules are still different: this establishes that same-day re-entry was harmful here, but does not isolate a separate historical return premium from the reset condition. Gate reset was promoted because it represents a genuinely new signal episode and did not sacrifice results in the production book. Full definitions, all nine policy arms, cost/capacity sensitivity, and legacy-rank results are in [docs/research/post-stop-reentry.md](docs/research/post-stop-reentry.md); source report: [`reports/daily_reentry_matrix.json`](reports/daily_reentry_matrix.json). ### Historical weekly production baseline (pre gate-reset) diff --git a/docs/research/README.md b/docs/research/README.md index 669b2a9..f223296 100644 --- a/docs/research/README.md +++ b/docs/research/README.md @@ -24,7 +24,7 @@ score, Structural S/R, the Gate Target Ladder, sentiment, fundamentals) is | 80/20 residual-momentum / 6m-volatility rank | Ranking tilt | Buys ~2pp CAGR over momentum-only; costs ~6pp drawdown | | 1.5× ATR initial stop | Real exit | Cuts losers fast | | 3× ATR trailing stop, 30-day max hold | Real exit | Best Sharpe of every exit tested | -| Post-stop normal gate reset | Re-entry policy | Stop always closes; a later gate failure and subsequent fresh qualification define the next signal episode. Sharpe 1.67 → 1.77 and CAGR 45.2% → 48.3% at production capacity 10. [Full study](post-stop-reentry.md) | +| Post-stop normal gate reset | Re-entry policy | Stop always closes; a later gate failure and subsequent fresh qualification define the next signal episode. The selected study arm reached Sharpe 1.77 / CAGR 48.3% at capacity 10; live scan-before-outcome timing is stricter (Sharpe 1.68 / CAGR 44.8% analogue). [Full study](post-stop-reentry.md) | | Max 10 concurrent positions, 1% risk per trade | Sizing | Cap never binds in practice | | Structural S/R | Human-facing product context | Clean, capped zones for charts and alerts; not read by the scanner | | Gate Target Ladder | Screening machinery | Volume-free transient proposals preserve the production candidate set exactly; never an exit | diff --git a/docs/research/post-stop-reentry.md b/docs/research/post-stop-reentry.md index cdf2edf..76dc449 100644 --- a/docs/research/post-stop-reentry.md +++ b/docs/research/post-stop-reentry.md @@ -29,7 +29,26 @@ cannot revive an older stop episode. This replaces the previously proposed fixed five-session lockdown. The normal reset counts an unqualified stop-day close when that close is observed after the stop. The stricter experiment, which required a failed close on a later session, -was not promoted. +was not promoted as the research policy. + +### Live scheduling boundary + +The live daily pipeline runs the R:R scan **before** Outcome Eval. A trade that +is closed at its initial stop by that Outcome Eval—or by an intraday evaluation +after the full scan—was therefore still open when the day's gate observation +ran. Its stop-day state cannot establish the failure. The earliest possible +failure is the next successful full scan, and a fresh qualification requires a +subsequent full scan. + +The study simulator closes positions before checking same-session re-entry +state, so its normal `gate_reset` arm can count the stop-day close. At this first +transition boundary, current live ordering is instead analogous to +`strict_gate_reset`. The distinction is material: the strict full-period row +recorded Sharpe 1.68, CAGR 44.8%, and 23.4% drawdown; its disjoint 2025+ row +recorded Sharpe 1.38, CAGR 32.9%, and 21.0% drawdown. The selected normal-reset +result (Sharpe 1.77) is therefore policy-study evidence, not exact live +scheduler-order parity. Changing that ordering would be a separate production +decision. ## Experiment design diff --git a/reports/README.md b/reports/README.md index ce27f3b..6d1697c 100644 --- a/reports/README.md +++ b/reports/README.md @@ -25,3 +25,19 @@ in Git history if a forensic reconstruction is ever necessary. The initial untracked `backtest-20260712-sr-detector-rewrite.json` is local-only and is intentionally not part of the repository. + +The 2026-07-17 post-stop re-entry decision is preserved in +`daily_reentry_matrix.json`. It is the canonical source for the nine-policy +daily replay, production-like full-universe ranking, the disjoint 2025+ book, +and the cost/capacity sensitivity matrix. The interpretation and production +decision live in +[`docs/research/post-stop-reentry.md`](../docs/research/post-stop-reentry.md). + +The earlier `post-stop-reentry-20260717.json`, +`post-stop-cooldown-sweep-20260717.json`, and +`gate-protected-stop-20260717.json` reports were removed as superseded +intermediate experiments. They used weekly/hybrid entry cadence or tested the +rejected stop-adjustment path, and add no decision evidence beyond the final +daily matrix and narrative. Their matching one-off runners were removed too. +All remain recoverable from Git history. Rebuildable candidate pickle caches +are intentionally ignored and must not be committed. diff --git a/reports/daily_reentry_cand.pk1 b/reports/daily_reentry_cand.pk1 deleted file mode 100644 index 3055210..0000000 Binary files a/reports/daily_reentry_cand.pk1 and /dev/null differ diff --git a/reports/gate-protected-stop-20260717.json b/reports/gate-protected-stop-20260717.json deleted file mode 100644 index 14331cb..0000000 --- a/reports/gate-protected-stop-20260717.json +++ /dev/null @@ -1,3173 +0,0 @@ -{ - "generated_at": "2026-07-17T10:32:13.434934+02:00", - "snapshot": "C:\\Workspace\\signal-platform\\backtest_snapshots\\prod.sqlite", - "period_start": "2024-07-01", - "tickers": 505, - "entry_candidates": 39867, - "qualified_candidates": 484, - "params": { - "entry_cadence_days": 5, - "setup_stop_atr_multiplier": 1.5, - "exit_policy": "atr_trail3", - "exit_atr_multiplier": 3.0, - "hold_days": 30, - "momentum_percentile_floor": 80.0, - "gate_refresh_information_cutoff": "previous close" - }, - "arms": [ - { - "arm": "baseline", - "starting_capital": 10000.0, - "final_equity": 26150.52, - "total_return_pct": 161.5, - "cagr_pct": 61.7, - "max_drawdown_pct": 11.8, - "sharpe": 2.4, - "trades": 162, - "win_rate": 42.6, - "avg_trade_pnl": 99.69, - "best_trade_r": 12.87, - "worst_trade_r": -2.56, - "best_trade_pnl": 2583.37, - "worst_trade_pnl": -429.69, - "avg_hold_days": 16.6, - "exit_reasons": { - "stop": 65, - "time": 43, - "trailing_stop": 54 - }, - "skipped_book_full": 5, - "spy_return_pct": 36.6, - "yearly_returns": [ - { - "year": 2024, - "return_pct": 24.5 - }, - { - "year": 2025, - "return_pct": 56.0 - }, - { - "year": 2026, - "return_pct": 34.6 - } - ], - "start_date": "2024-07-01", - "end_date": "2026-07-02" - }, - { - "arm": "cooldown_5", - "starting_capital": 10000.0, - "final_equity": 27013.52, - "total_return_pct": 170.1, - "cagr_pct": 64.3, - "max_drawdown_pct": 11.8, - "sharpe": 2.51, - "trades": 163, - "win_rate": 42.3, - "avg_trade_pnl": 104.38, - "best_trade_r": 12.87, - "worst_trade_r": -2.56, - "best_trade_pnl": 2668.62, - "worst_trade_pnl": -430.34, - "avg_hold_days": 16.6, - "exit_reasons": { - "stop": 67, - "time": 43, - "trailing_stop": 53 - }, - "skipped_book_full": 5, - "spy_return_pct": 36.6, - "yearly_returns": [ - { - "year": 2024, - "return_pct": 23.7 - }, - { - "year": 2025, - "return_pct": 57.5 - }, - { - "year": 2026, - "return_pct": 38.7 - } - ], - "start_date": "2024-07-01", - "end_date": "2026-07-02", - "reentry_cooldown_days": 5, - "skipped_cooldown": 5 - }, - { - "arm": "cooldown_10", - "starting_capital": 10000.0, - "final_equity": 25830.23, - "total_return_pct": 158.3, - "cagr_pct": 60.7, - "max_drawdown_pct": 11.0, - "sharpe": 2.37, - "trades": 154, - "win_rate": 39.6, - "avg_trade_pnl": 102.79, - "best_trade_r": 12.87, - "worst_trade_r": -2.56, - "best_trade_pnl": 2539.73, - "worst_trade_pnl": -451.67, - "avg_hold_days": 15.9, - "exit_reasons": { - "stop": 66, - "time": 37, - "trailing_stop": 51 - }, - "skipped_book_full": 5, - "spy_return_pct": 36.6, - "yearly_returns": [ - { - "year": 2024, - "return_pct": 23.2 - }, - { - "year": 2025, - "return_pct": 54.6 - }, - { - "year": 2026, - "return_pct": 35.5 - } - ], - "start_date": "2024-07-01", - "end_date": "2026-07-02", - "reentry_cooldown_days": 10, - "skipped_cooldown": 15 - }, - { - "arm": "gate_protected_stop", - "starting_capital": 10000.0, - "final_equity": 27792.18, - "total_return_pct": 177.9, - "cagr_pct": 66.7, - "max_drawdown_pct": 11.8, - "sharpe": 2.53, - "trades": 154, - "win_rate": 44.2, - "avg_trade_pnl": 115.53, - "best_trade_r": 12.87, - "worst_trade_r": -2.56, - "best_trade_pnl": 2720.83, - "worst_trade_pnl": -455.88, - "avg_hold_days": 17.4, - "exit_reasons": { - "stop": 57, - "time": 42, - "trailing_stop": 55 - }, - "skipped_book_full": 5, - "spy_return_pct": 36.6, - "yearly_returns": [ - { - "year": 2024, - "return_pct": 32.6 - }, - { - "year": 2025, - "return_pct": 55.0 - }, - { - "year": 2026, - "return_pct": 35.2 - } - ], - "start_date": "2024-07-01", - "end_date": "2026-07-02", - "stop_refresh_attempts": 62, - "stop_refreshes": 7, - "stop_refresh_same_bar_hits": 2, - "trade_details": [ - { - "symbol": "VLO", - "entry": 157.96, - "initial_stop": 151.69150000000002, - "active_stop": 151.69150000000002, - "fill": 151.69150000000002, - "pnl": -40.905296801020604, - "r": -1.0, - "hold": 3, - "reason": "stop", - "stop_refreshes": 0, - "entry_date": "2024-07-02", - "exit_date": "2024-07-08" - }, - { - "symbol": "HOOD", - "entry": 22.79, - "initial_stop": 21.1907, - "active_stop": 21.4047, - "fill": 21.4047, - "pnl": -89.3825236040769, - "r": -0.8661914587632097, - "hold": 16, - "reason": "trailing_stop", - "stop_refreshes": 0, - "entry_date": "2024-07-01", - "exit_date": "2024-07-24" - }, - { - "symbol": "APP", - "entry": 83.68, - "initial_stop": 78.4555, - "active_stop": 78.4555, - "fill": 77.78, - "pnl": -115.76397760040211, - "r": -1.1292946693463486, - "hold": 16, - "reason": "stop", - "stop_refreshes": 0, - "entry_date": "2024-07-02", - 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"active_stop": 57.1896, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - }, - { - "symbol": "NEM", - "stop_date": "2026-05-19", - "gate_asof_date": "2026-05-18", - "momentum_percentile": 96.81, - "gate_core_passed": false, - "gate_passed": false, - "active_stop": 106.9009, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - }, - { - "symbol": "MRNA", - "stop_date": "2026-05-19", - "gate_asof_date": "2026-05-18", - "momentum_percentile": 96.41, - "gate_core_passed": false, - "gate_passed": false, - "active_stop": 47.3288, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - }, - { - "symbol": "APA", - "stop_date": "2026-05-26", - "gate_asof_date": "2026-05-22", - "momentum_percentile": 97.6, - "gate_core_passed": false, - "gate_passed": false, - "active_stop": 37.5838, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - }, - { - "symbol": "CVS", - "stop_date": "2026-05-26", - "gate_asof_date": "2026-05-22", - "momentum_percentile": 80.64, - "gate_core_passed": false, - "gate_passed": false, - "active_stop": 92.303, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - }, - { - "symbol": "OXY", - "stop_date": "2026-05-27", - "gate_asof_date": "2026-05-26", - "momentum_percentile": 92.02, - "gate_core_passed": false, - "gate_passed": false, - "active_stop": 56.7075, - "replacement_stop": null, - "lower_stop": false, - "same_bar_survives": false, - "replacement_risk_r": null - } - ] - }, - "note": "The gate-protected arm recalculates the gate at an initial-stop touch using only data available through the previous close. It accepts only a lower stop from a newly valid long setup and checks that replacement against the same bar. It does not cancel stops using the later same-day close." -} diff --git a/reports/post-stop-cooldown-sweep-20260717.json b/reports/post-stop-cooldown-sweep-20260717.json deleted file mode 100644 index 32f1a86..0000000 --- a/reports/post-stop-cooldown-sweep-20260717.json +++ /dev/null @@ -1,17494 +0,0 @@ -{ - "generated_at": "2026-07-17T12:15:02.918220+02:00", - "snapshot": "C:\\Workspace\\signal-platform\\backtest_snapshots\\prod.sqlite", - "period_start": "2024-07-01", - "tickers": 505, - "entry_candidates": 39867, - "qualified_candidates": 484, - "params": { - "initial_entry_cadence_days": 5, - "post_stop_evaluation_cadence_days": 1, - "setup_stop_atr_multiplier": 1.5, - "exit_policy": "atr_trail3", - "exit_atr_multiplier": 3.0, - "hold_days": 30, - "cost_per_side_pct": 0.1, - "momentum_percentile_floor": 80.0, - "reclaim_atr_buffer": 0.25, - "cooldown_sessions": [ - 3, - 5, - 7, - 10 - ] - }, - "arms": [ - { - "arm": "immediate", - "starting_capital": 10000.0, - "final_equity": 23771.78, - 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Only tickers stopped at their initial stop switch to daily evaluation, which isolates next-day/same-episode re-entry churn. A cooldown of N sessions permits the first re-entry at wait_sessions=N. Gate reset requires at least one unqualified daily close before requalification. The reclaim arm alternatively accepts a close above stop-day high + 0.25 ATR only when the new setup stop is above the prior stop." -} diff --git a/reports/post-stop-reentry-20260717.json b/reports/post-stop-reentry-20260717.json deleted file mode 100644 index 6e098be..0000000 --- a/reports/post-stop-reentry-20260717.json +++ /dev/null @@ -1,14691 +0,0 @@ -{ - "generated_at": "2026-07-17T11:26:27.212863+02:00", - "snapshot": "C:\\Workspace\\signal-platform\\backtest_snapshots\\prod.sqlite", - "period_start": "2024-07-01", - "tickers": 505, - "entry_candidates": 39867, - "qualified_candidates": 484, - "params": { - "initial_entry_cadence_days": 5, - "post_stop_evaluation_cadence_days": 1, - "setup_stop_atr_multiplier": 1.5, - "exit_policy": "atr_trail3", - "exit_atr_multiplier": 3.0, - "hold_days": 30, - "cost_per_side_pct": 0.1, - "momentum_percentile_floor": 80.0, - "reclaim_atr_buffer": 0.25 - }, - "arms": [ - { - "arm": "immediate", - "starting_capital": 10000.0, - "final_equity": 23771.78, - 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"fill": 92.303, - "pnl": -74.79424493713188, - "r": -1.0, - "hold": 5, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": false, - "reentry_wait_sessions": null, - "transaction_cost": 3.6341078627983445, - "entry_date": "2026-05-18", - "exit_date": "2026-05-26" - }, - { - "symbol": "OXY", - "entry": 59.7, - "initial_stop": 56.7075, - "active_stop": 56.7075, - "fill": 56.6, - "pnl": -251.20280864640088, - "r": -1.0359231411862997, - "hold": 6, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": false, - "reentry_wait_sessions": null, - "transaction_cost": 9.083383591573053, - "entry_date": "2026-05-18", - "exit_date": "2026-05-27" - }, - { - "symbol": "MRK", - "entry": 119.72, - "initial_stop": 115.1645, - "active_stop": 115.1645, - "fill": 115.1645, - "pnl": -183.03019291563007, - "r": -1.0, - "hold": 4, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 27, - "transaction_cost": 8.97442686445969, - "entry_date": "2026-05-26", - "exit_date": "2026-06-01" - }, - { - "symbol": "ADM", - "entry": 70.03, - "initial_stop": 66.99940000000001, - "active_stop": 77.0729, - "fill": 80.92, - "pnl": 449.4097505673201, - "r": 3.5933478519105218, - "hold": 30, - "reason": "time", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 11, - "transaction_cost": 6.3169835179216935, - "entry_date": "2026-04-23", - "exit_date": "2026-06-05" - }, - { - "symbol": "FSLR", - "entry": 211.39, - "initial_stop": 197.15935, - "active_stop": 274.3201, - "fill": 274.3201, - "pnl": 312.368367961756, - "r": 4.422152185599397, - "hold": 25, - "reason": "trailing_stop", - "stop_refreshes": 0, - "is_reentry": false, - "reentry_wait_sessions": null, - "transaction_cost": 2.4296893841466014, - "entry_date": "2026-05-04", - "exit_date": "2026-06-09" - }, - { - "symbol": "APA", - "entry": 38.33, - "initial_stop": 35.997499999999995, - "active_stop": 35.997499999999995, - "fill": 35.997499999999995, - "pnl": -240.14700439342755, - "r": -1.0, - "hold": 4, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 6, - "transaction_cost": 7.416205136866876, - "entry_date": "2026-06-03", - "exit_date": "2026-06-09" - }, - { - "symbol": "IVZ", - "entry": 25.86, - "initial_stop": 24.47325, - "active_stop": 26.0541, - "fill": 27.46, - "pnl": 28.561543176208364, - "r": 1.1537768162970992, - "hold": 30, - "reason": "time", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 110, - "transaction_cost": 0.984626090823848, - "entry_date": "2026-04-28", - "exit_date": "2026-06-10" - }, - { - "symbol": "MRK", - "entry": 120.26, - "initial_stop": 115.53500000000001, - "active_stop": 115.53500000000001, - "fill": 115.53500000000001, - "pnl": -23.38602755882761, - "r": -1.0, - "hold": 7, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 3, - "transaction_cost": 1.1115775532417183, - "entry_date": "2026-06-04", - "exit_date": "2026-06-15" - }, - { - "symbol": "OXY", - "entry": 56.93, - "initial_stop": 54.093199999999996, - "active_stop": 54.093199999999996, - "fill": 53.45, - "pnl": -213.13910778459226, - "r": -1.226734348561757, - "hold": 6, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 7, - "transaction_cost": 6.5525918474544, - "entry_date": "2026-06-05", - "exit_date": "2026-06-15" - }, - { - "symbol": "APA", - "entry": 38.0, - "initial_stop": 35.6483, - "active_stop": 35.6483, - "fill": 34.73, - "pnl": -323.3928301692485, - "r": -1.3904834800357195, - "hold": 3, - "reason": "stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 1, - "transaction_cost": 7.036272908134793, - "entry_date": "2026-06-10", - "exit_date": "2026-06-15" - }, - { - "symbol": "CHRW", - "entry": 178.13, - "initial_stop": 167.6753, - "active_stop": 176.1996, - "fill": 176.1996, - "pnl": -43.08815055527362, - "r": -0.18464422699838265, - "hold": 22, - "reason": "trailing_stop", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 13, - "transaction_cost": 6.682369393292685, - "entry_date": "2026-05-21", - "exit_date": "2026-06-24" - }, - { - "symbol": "BIIB", - "entry": 191.91, - "initial_stop": 182.80965, - "active_stop": 196.9144, - "fill": 209.74, - "pnl": 424.4280835044584, - "r": 1.9592653029828555, - "hold": 30, - "reason": "time", - "stop_refreshes": 0, - "is_reentry": false, - "reentry_wait_sessions": null, - "transaction_cost": 9.781278189820913, - "entry_date": "2026-05-18", - "exit_date": "2026-07-01" - }, - { - "symbol": "MRNA", - "entry": 47.61, - "initial_stop": 43.1472, - "active_stop": 65.42330000000001, - "fill": 79.76, - "pnl": 1647.8036069715545, - "r": 7.2039974903647925, - "hold": 25, - "reason": "open_at_end", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 5, - "transaction_cost": 6.554138289702216, - "entry_date": "2026-05-27", - "exit_date": "2026-07-02" - }, - { - "symbol": "CVS", - "entry": 92.07, - "initial_stop": 88.62825, - "active_stop": 97.742, - "fill": 104.72, - "pnl": 349.27964992039426, - "r": 3.675455800101695, - "hold": 25, - "reason": "open_at_end", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 1, - "transaction_cost": 5.519439751504585, - "entry_date": "2026-05-27", - "exit_date": "2026-07-02" - }, - { - "symbol": "MRK", - "entry": 119.6, - "initial_stop": 114.81635, - "active_stop": 119.5283, - "fill": 129.56, - "pnl": 373.7976793776763, - "r": 2.0820921263052314, - "hold": 7, - "reason": "open_at_end", - "stop_refreshes": 0, - "is_reentry": true, - "reentry_wait_sessions": 5, - "transaction_cost": 9.590872653008581, - "entry_date": "2026-06-23", - "exit_date": "2026-07-02" - } - ] - } - ], - "note": "Initial opportunities retain the validated weekly replay cadence. Only tickers stopped at their initial stop switch to daily evaluation, which isolates next-day/same-episode re-entry churn. Gate reset requires at least one unqualified daily close before requalification. The reclaim arm alternatively accepts a close above stop-day high + 0.25 ATR only when the new setup stop is above the prior stop." -} diff --git a/scripts/run_gate_protected_stop_study.py b/scripts/run_gate_protected_stop_study.py deleted file mode 100644 index d674589..0000000 --- a/scripts/run_gate_protected_stop_study.py +++ /dev/null @@ -1,422 +0,0 @@ -"""Targeted offline study of a gate-conditioned initial-stop refresh. - -The study replays production entries only for the requested period. Whenever -an initial stop is touched, it rebuilds that ticker's setup using bars through -the previous close and recomputes the production momentum gate across the whole -historical universe. If the gate still passes and the new setup has a lower -valid stop, the simulator adopts it and checks it against the same day's low. - -This is causal: no value from the stop day's eventual close is used to cancel -an intraday stop. The snapshot is read-only and no live settings are changed. -""" - -from __future__ import annotations - -import argparse -import asyncio -import bisect -import json -import multiprocessing -import os -import sys -from collections import Counter -from concurrent.futures import ProcessPoolExecutor, as_completed -from datetime import date, datetime -from pathlib import Path -from types import SimpleNamespace -from typing import Any - -from sqlalchemy import select -from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine - -ROOT = Path(__file__).resolve().parents[1] -if str(ROOT) not in sys.path: - sys.path.insert(0, str(ROOT)) - - -def _sqlite_url(path: Path) -> str: - return f"sqlite+aiosqlite:///{path.resolve().as_posix()}" - - -def _parse_args() -> argparse.Namespace: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument("snapshot") - parser.add_argument("--start-date", default="2024-07-01") - parser.add_argument("--workers", type=int, default=6) - parser.add_argument("--out", default=None) - parser.add_argument("--quiet", action="store_true") - return parser.parse_args() - - -def _default_output_path() -> Path: - stamp = datetime.now().strftime("%Y%m%d-%H%M%S") - return Path("reports") / f"gate-protected-stop-{stamp}.json" - - -class GateStopRefresher: - """Point-in-time gate and replacement-stop calculator for stop events.""" - - def __init__( - self, - prices: dict[str, tuple], - recommendation_config: dict, - activation: dict, - benchmark_closes: dict[date, float], - ) -> None: - from app.services import backtest_service as bt - - self.bt = bt - self.prices = prices - self.recommendation_config = recommendation_config - self.activation = activation - self.benchmark_closes = benchmark_closes - self.threshold = float(activation.get("min_momentum_percentile", 80.0)) - self.dates = { - symbol: [date.fromordinal(value) for value in columns[0]] - for symbol, columns in prices.items() - } - self.index_of = { - symbol: {value: index for index, value in enumerate(columns[0])} - for symbol, columns in prices.items() - } - self.percentile_cache: dict[int, dict[str, float]] = {} - self.setup_cache: dict[tuple[str, int], dict | None] = {} - self.events: list[dict[str, Any]] = [] - - def _momentum_percentiles(self, asof_ord: int) -> dict[str, float]: - cached = self.percentile_cache.get(asof_ord) - if cached is not None: - return cached - - values: dict[str, float] = {} - for symbol, columns in self.prices.items(): - idx = bisect.bisect_right(columns[0], asof_ord) - 1 - if idx < 252: - continue - closes = columns[4] - value = self.bt._residual_momentum_12_1( - self.dates[symbol], closes, idx, self.benchmark_closes - ) - if value is None and closes[idx - 252] > 0: - value = closes[idx - 21] / closes[idx - 252] - 1.0 - if value is not None: - values[symbol] = float(value) - - ordered = sorted(values, key=lambda symbol: values[symbol]) - denominator = len(ordered) - 1 - percentiles = { - symbol: (rank / denominator * 100.0) if denominator > 0 else 100.0 - for rank, symbol in enumerate(ordered) - } - self.percentile_cache[asof_ord] = percentiles - return percentiles - - def _long_setup(self, symbol: str, asof_idx: int) -> dict | None: - columns = self.prices[symbol] - asof_ord = columns[0][asof_idx] - key = (symbol, asof_ord) - if key in self.setup_cache: - return self.setup_cache[key] - - records = [ - SimpleNamespace( - date=date.fromordinal(o), - open=op, - high=high, - low=low, - close=close, - volume=volume, - ) - for o, op, high, low, close, volume in zip( - columns[0][: asof_idx + 1], - columns[1][: asof_idx + 1], - columns[2][: asof_idx + 1], - columns[3][: asof_idx + 1], - columns[4][: asof_idx + 1], - columns[5][: asof_idx + 1], - ) - ] - setups = self.bt._window_setups( - records, self.recommendation_config, self.activation - ) - setup = next((row for row in setups if row["direction"] == "long"), None) - self.setup_cache[key] = setup - return setup - - def __call__( - self, - symbol: str, - stop_ord: int, - active_stop: float, - position: dict, - bar: Any, - ) -> float | None: - columns = self.prices[symbol] - stop_idx = self.index_of[symbol].get(stop_ord) - if stop_idx is None: - stop_idx = bisect.bisect_left(columns[0], stop_ord) - asof_idx = stop_idx - 1 - if asof_idx < self.bt.MIN_LOOKBACK - 1: - return None - - asof_ord = columns[0][asof_idx] - setup = self._long_setup(symbol, asof_idx) - momentum_pct = self._momentum_percentiles(asof_ord).get(symbol) - gate_passed = bool( - setup is not None - and self.bt._momentum_qualifies( - { - "meets_core": setup["meets_core"], - "direction": "long", - self.bt.PRODUCTION_PERCENTILE_KEY: momentum_pct, - }, - self.threshold, - ) - ) - new_stop = float(setup["stop"]) if gate_passed and setup is not None else None - lower_stop = bool(new_stop is not None and new_stop < active_stop - 1e-9) - original_risk = float(position["entry"] - position["initial_stop"]) - replacement_risk_r = ( - (float(position["entry"]) - new_stop) / original_risk - if lower_stop and original_risk > 0 and new_stop is not None - else None - ) - self.events.append({ - "symbol": symbol, - "stop_date": date.fromordinal(stop_ord).isoformat(), - "gate_asof_date": date.fromordinal(asof_ord).isoformat(), - "momentum_percentile": round(momentum_pct, 2) - if momentum_pct is not None - else None, - "gate_core_passed": bool(setup and setup["meets_core"]), - "gate_passed": gate_passed, - "active_stop": round(active_stop, 4), - "replacement_stop": round(new_stop, 4) if new_stop is not None else None, - "lower_stop": lower_stop, - "same_bar_survives": bool(lower_stop and bar.low > new_stop), - "replacement_risk_r": round(replacement_risk_r, 3) - if replacement_risk_r is not None - else None, - }) - return new_stop - - -def _arm(label: str, sim: dict) -> dict: - trade_details = sim.pop("trade_details", None) - row = {"arm": label, **sim} - if trade_details is not None: - row["trade_details"] = trade_details - return row - - -def _rescued_trade_summary(trades: list[dict]) -> dict: - rescued = [trade for trade in trades if trade.get("stop_refreshes", 0) > 0] - rs = [float(trade["r"]) for trade in rescued] - return { - "trades": len(rescued), - "wins": sum(value > 0 for value in rs), - "win_rate": round(sum(value > 0 for value in rs) / len(rs) * 100.0, 1) - if rs - else None, - "avg_r": round(sum(rs) / len(rs), 3) if rs else None, - "total_r": round(sum(rs), 2) if rs else None, - "worst_r": round(min(rs), 2) if rs else None, - "best_r": round(max(rs), 2) if rs else None, - "exit_reasons": dict(Counter(trade["reason"] for trade in rescued)), - } - - -async def _main() -> None: - args = _parse_args() - snapshot = Path(args.snapshot) - if not snapshot.exists(): - raise SystemExit(f"Snapshot not found: {snapshot}") - try: - start_date = date.fromisoformat(args.start_date) - except ValueError as exc: - raise SystemExit("--start-date must use YYYY-MM-DD") from exc - - os.environ["BACKTEST_SNAPSHOT_OFFLINE"] = "1" - os.environ["BACKTEST_ALLOW_SPAWN"] = "1" - - from app.models.ticker import Ticker - from app.services import backtest_service as bt - from app.services.admin_service import get_activation_config - from app.services.paper_trade_service import get_exit_policy - from app.services.recommendation_service import get_recommendation_config - - engine = create_async_engine(_sqlite_url(snapshot), pool_pre_ping=True) - Session = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False) - try: - async with Session() as db: - recommendation_config = await get_recommendation_config(db) - activation = await get_activation_config(db) - exit_config = await get_exit_policy(db) - benchmark_closes = await bt._load_benchmark_closes_for_backtest( - db, days=None, refresh=False - ) - ticker_result = await db.execute(select(Ticker).order_by(Ticker.symbol)) - symbols = [ticker.symbol for ticker in ticker_result.scalars().all()] - prices: dict[str, tuple] = {} - for index, symbol in enumerate(symbols, 1): - columns = await bt._fetch_columns(db, symbol) - if columns is not None: - prices[symbol] = columns - if not args.quiet and index % 50 == 0: - print(f"loaded prices: {index}/{len(symbols)}", flush=True) - finally: - await engine.dispose() - - candidates: list[dict] = [] - workers = max(1, min(int(args.workers), multiprocessing.cpu_count() - 1)) - context = multiprocessing.get_context("spawn") - with ProcessPoolExecutor(max_workers=workers, mp_context=context) as pool: - futures = { - pool.submit( - bt._replay_candidates_for_period, - symbol, - columns, - recommendation_config, - activation, - benchmark_closes, - start_date, - ): symbol - for symbol, columns in prices.items() - } - for index, future in enumerate(as_completed(futures), 1): - candidates.extend(future.result()) - if not args.quiet and index % 25 == 0: - print(f"replayed tickers: {index}/{len(futures)}", flush=True) - - bt._assign_momentum_percentiles(candidates) - bt._assign_residual_momentum_percentiles(candidates) - bt._assign_low_volatility_percentiles(candidates) - bt._assign_activation_momentum_percentiles(candidates) - bt._assign_residual_high_vol_blend(candidates) - threshold = float(activation.get("min_momentum_percentile", 80.0)) - for candidate in candidates: - candidate["qualified"] = bt._momentum_qualifies(candidate, threshold) - - strategy = next( - row for row in bt.PORTFOLIO_MONITOR_STRATEGIES if row.get("is_production") - ) - entry_config = bt._entry_variant_config(str(strategy["entry_variant"])) - if entry_config is None: - raise RuntimeError("Production entry configuration missing") - exit_policy = bt.LIVE_EXIT_MODE_TO_SIM.get( - str(exit_config.get("mode", "atr_trailing")), "atr_trail3" - ) - hold_days = int(exit_config.get("hold_days", max(bt.TIME_EXIT_DAYS))) - trail_multiplier = float( - exit_config.get("atr_multiplier", bt.ATR_TRAIL_MULTIPLIER) - ) - sim_kwargs = { - "qualified_fn": None, - "ranking_key": str( - entry_config.get("ranking_key") or entry_config["percentile_key"] - ), - "max_positions": int(entry_config["max_positions"]), - "risk_per_trade": float(entry_config["risk_per_trade"]), - "atr_trail_multiplier": trail_multiplier, - "start_date": start_date, - } - - baseline = bt._simulate_portfolio( - candidates, prices, benchmark_closes, exit_policy, hold_days, **sim_kwargs - ) - cooldown_5 = bt._simulate_portfolio( - candidates, - prices, - benchmark_closes, - exit_policy, - hold_days, - reentry_cooldown_sessions=5, - **sim_kwargs, - ) - cooldown_10 = bt._simulate_portfolio( - candidates, - prices, - benchmark_closes, - exit_policy, - hold_days, - reentry_cooldown_sessions=10, - **sim_kwargs, - ) - refresher = GateStopRefresher( - prices, recommendation_config, activation, benchmark_closes - ) - gate_protected = bt._simulate_portfolio( - candidates, - prices, - benchmark_closes, - exit_policy, - hold_days, - initial_stop_refresh_fn=refresher, - include_trades=True, - **sim_kwargs, - ) - if any(row is None for row in (baseline, cooldown_5, cooldown_10, gate_protected)): - raise RuntimeError("A study arm produced no trades") - - gate_trades = list(gate_protected.get("trade_details") or []) - event_counts = Counter() - for event in refresher.events: - event_counts["stop_touches"] += 1 - if event["gate_passed"]: - event_counts["gate_passed"] += 1 - if event["lower_stop"]: - event_counts["lower_stop"] += 1 - if event["same_bar_survives"]: - event_counts["same_bar_survives"] += 1 - - report = { - "generated_at": datetime.now().astimezone().isoformat(), - "snapshot": str(snapshot.resolve()), - "period_start": start_date.isoformat(), - "tickers": len(prices), - "entry_candidates": len(candidates), - "qualified_candidates": sum(bool(row["qualified"]) for row in candidates), - "params": { - "entry_cadence_days": bt.STEP_DAYS, - "setup_stop_atr_multiplier": bt.ATR_MULTIPLIER, - "exit_policy": exit_policy, - "exit_atr_multiplier": trail_multiplier, - "hold_days": hold_days, - "momentum_percentile_floor": threshold, - "gate_refresh_information_cutoff": "previous close", - }, - "arms": [ - _arm("baseline", baseline), - _arm("cooldown_5", cooldown_5), - _arm("cooldown_10", cooldown_10), - _arm("gate_protected_stop", gate_protected), - ], - "gate_stop_events": { - **dict(event_counts), - "unique_symbols": len({event["symbol"] for event in refresher.events}), - "rescued_trade_outcomes": _rescued_trade_summary(gate_trades), - "events": refresher.events, - }, - "note": ( - "The gate-protected arm recalculates the gate at an initial-stop touch " - "using only data available through the previous close. It accepts only " - "a lower stop from a newly valid long setup and checks that replacement " - "against the same bar. It does not cancel stops using the later same-day close." - ), - } - output = Path(args.out) if args.out else _default_output_path() - output.parent.mkdir(parents=True, exist_ok=True) - output.write_text(json.dumps(report, indent=2) + "\n", encoding="utf-8") - - print(f"Report written: {output}") - for arm in report["arms"]: - print( - f"{arm['arm']}: Sharpe {arm['sharpe']}, CAGR {arm['cagr_pct']}%, " - f"DD {arm['max_drawdown_pct']}%, trades {arm['trades']}" - ) - print(f"gate stop events: {dict(event_counts)}") - print(f"rescued outcomes: {report['gate_stop_events']['rescued_trade_outcomes']}") - - -if __name__ == "__main__": - asyncio.run(_main()) diff --git a/scripts/run_post_stop_reentry_study.py b/scripts/run_post_stop_reentry_study.py deleted file mode 100644 index daffba9..0000000 --- a/scripts/run_post_stop_reentry_study.py +++ /dev/null @@ -1,541 +0,0 @@ -"""Offline event study for stateful post-stop re-entry policies. - -Initial entries keep the validated weekly production cadence. After an initial -stop, the affected ticker is evaluated on every subsequent daily close. This -isolates the exact churn problem without changing the rest of the portfolio. -All arms retain the hard stop, production position sizing, 3x ATR trail, and -round-trip transaction costs. -""" - -from __future__ import annotations - -import argparse -import asyncio -import bisect -import json -import multiprocessing -import os -import pickle -import sys -from collections import Counter -from concurrent.futures import ProcessPoolExecutor, as_completed -from datetime import date, datetime -from pathlib import Path -from types import SimpleNamespace -from typing import Any - -from sqlalchemy import select -from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine - -ROOT = Path(__file__).resolve().parents[1] -if str(ROOT) not in sys.path: - sys.path.insert(0, str(ROOT)) - -RECLAIM_ATR_BUFFER = 0.25 - - -def _sqlite_url(path: Path) -> str: - return f"sqlite+aiosqlite:///{path.resolve().as_posix()}" - - -def _parse_args() -> argparse.Namespace: - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument("snapshot") - parser.add_argument("--start-date", default="2024-07-01") - parser.add_argument("--workers", type=int, default=6) - parser.add_argument("--out", default=None) - parser.add_argument( - "--candidate-cache", - default=None, - help="Optional pickle cache for the expensive weekly candidate replay.", - ) - parser.add_argument("--quiet", action="store_true") - parser.add_argument( - "--cooldowns", - type=int, - nargs="+", - default=None, - help=( - "Run an immediate baseline plus the given cooldown lengths instead " - "of the gate-reset policy study (for example: 3 5 7 10)." - ), - ) - return parser.parse_args() - - -def _default_output_path() -> Path: - stamp = datetime.now().strftime("%Y%m%d-%H%M%S") - return Path("reports") / f"post-stop-reentry-{stamp}.json" - - -class DailySetupEngine: - """Point-in-time daily setup and universe-rank cache.""" - - def __init__( - self, - prices: dict[str, tuple], - recommendation_config: dict, - activation: dict, - benchmark_closes: dict[date, float], - ) -> None: - from app.services import backtest_service as bt - - self.bt = bt - self.prices = prices - self.recommendation_config = recommendation_config - self.activation = activation - self.benchmark_closes = benchmark_closes - self.threshold = float(activation.get("min_momentum_percentile", 80.0)) - self.dates = { - symbol: [date.fromordinal(value) for value in columns[0]] - for symbol, columns in prices.items() - } - self.index_of = { - symbol: {value: index for index, value in enumerate(columns[0])} - for symbol, columns in prices.items() - } - self.rank_cache: dict[int, dict[str, tuple[float, float]]] = {} - self.candidate_cache: dict[tuple[str, int], dict | None] = {} - self.atr_cache: dict[tuple[str, int], float | None] = {} - - @staticmethod - def _percentiles(values: dict[str, float]) -> dict[str, float]: - ordered = sorted(values, key=lambda symbol: values[symbol]) - denominator = len(ordered) - 1 - return { - symbol: (rank / denominator * 100.0) if denominator > 0 else 100.0 - for rank, symbol in enumerate(ordered) - } - - def _ranks(self, asof_ord: int) -> dict[str, tuple[float, float]]: - cached = self.rank_cache.get(asof_ord) - if cached is not None: - return cached - - momentum_values: dict[str, float] = {} - volatility_values: dict[str, float] = {} - for symbol, columns in self.prices.items(): - idx = bisect.bisect_right(columns[0], asof_ord) - 1 - if idx < 0: - continue - closes = columns[4] - if idx >= 252: - momentum = self.bt._residual_momentum_12_1( - self.dates[symbol], closes, idx, self.benchmark_closes - ) - if momentum is None and closes[idx - 252] > 0: - momentum = closes[idx - 21] / closes[idx - 252] - 1.0 - if momentum is not None: - momentum_values[symbol] = float(momentum) - volatility = self.bt._realized_vol_6m(closes, idx) - if volatility is not None: - volatility_values[symbol] = float(volatility) - - momentum_pct = self._percentiles(momentum_values) - volatility_pct = self._percentiles(volatility_values) - ranks = { - symbol: (momentum_pct[symbol], volatility_pct.get(symbol, 0.0)) - for symbol in momentum_pct - } - self.rank_cache[asof_ord] = ranks - return ranks - - def atr(self, symbol: str, asof_ord: int) -> float | None: - key = (symbol, asof_ord) - if key in self.atr_cache: - return self.atr_cache[key] - columns = self.prices[symbol] - idx = self.index_of[symbol].get(asof_ord) - if idx is None: - idx = bisect.bisect_right(columns[0], asof_ord) - 1 - if idx < 0: - self.atr_cache[key] = None - return None - try: - value = self.bt.compute_atr( - columns[2][: idx + 1], - columns[3][: idx + 1], - columns[4][: idx + 1], - )["atr"] - result = float(value) if value and value > 0 else None - except Exception: - result = None - self.atr_cache[key] = result - return result - - def candidate(self, symbol: str, asof_ord: int) -> dict | None: - key = (symbol, asof_ord) - if key in self.candidate_cache: - cached = self.candidate_cache[key] - return dict(cached) if cached is not None else None - - columns = self.prices[symbol] - idx = self.index_of[symbol].get(asof_ord) - if idx is None or idx < self.bt.MIN_LOOKBACK - 1: - self.candidate_cache[key] = None - return None - records = [ - SimpleNamespace( - date=date.fromordinal(o), - open=op, - high=high, - low=low, - close=close, - volume=volume, - ) - for o, op, high, low, close, volume in zip( - columns[0][: idx + 1], - columns[1][: idx + 1], - columns[2][: idx + 1], - columns[3][: idx + 1], - columns[4][: idx + 1], - columns[5][: idx + 1], - ) - ] - setups = self.bt._window_setups( - records, self.recommendation_config, self.activation - ) - setup = next((row for row in setups if row["direction"] == "long"), None) - rank = self._ranks(asof_ord).get(symbol) - gate_passed = bool( - setup is not None - and rank is not None - and self.bt._momentum_qualifies( - { - "meets_core": setup["meets_core"], - "direction": "long", - self.bt.PRODUCTION_PERCENTILE_KEY: rank[0], - }, - self.threshold, - ) - ) - if not gate_passed or setup is None or rank is None: - self.candidate_cache[key] = None - return None - - strategy_rank = ( - rank[0] * self.bt.STRATEGY_RANK_MOMENTUM_WEIGHT - + rank[1] * (1.0 - self.bt.STRATEGY_RANK_MOMENTUM_WEIGHT) - ) - candidate = { - "symbol": symbol, - "date": date.fromordinal(asof_ord).isoformat(), - "direction": "long", - "entry": float(setup["entry"]), - "stop": float(setup["stop"]), - "target": float(setup["target"]), - "qualified": True, - self.bt.PRODUCTION_PERCENTILE_KEY: rank[0], - self.bt.RESIDUAL_HIGH_VOL_BLEND_80_20_KEY: strategy_rank, - } - self.candidate_cache[key] = candidate - return dict(candidate) - - -class ReentryPolicy: - def __init__(self, name: str, engine: DailySetupEngine) -> None: - self.name = name - self.engine = engine - self.checks = 0 - self.gate_passes = 0 - self.emitted = Counter() - - def __call__( - self, - symbol: str, - asof_ord: int, - state: dict, - bar: Any, - ) -> dict | None: - self.checks += 1 - if "reentry_trigger" not in state: - stop_atr = self.engine.atr(symbol, state["stop_ord"]) - state["reentry_trigger"] = ( - state["stop_day_high"] + RECLAIM_ATR_BUFFER * stop_atr - if stop_atr is not None - else state["stop_day_high"] - ) - - candidate = self.engine.candidate(symbol, asof_ord) - if candidate is None: - state["gate_went_unqualified"] = True - return None - self.gate_passes += 1 - - reason: str | None = None - sessions = int(state["sessions_since_stop"]) - if self.name == "immediate": - reason = "gate_still_or_again_qualified" - elif self.name.startswith("cooldown_"): - cooldown_sessions = int(self.name.removeprefix("cooldown_")) - if sessions >= cooldown_sessions: - reason = f"{cooldown_sessions}_session_cooldown_complete" - elif self.name == "gate_reset": - if state["gate_went_unqualified"]: - reason = "gate_failed_then_requalified" - elif self.name == "gate_reset_or_reclaim": - if state["gate_went_unqualified"]: - reason = "gate_failed_then_requalified" - elif ( - bar.close > state["reentry_trigger"] - and float(candidate["stop"]) > state["previous_stop"] - ): - reason = "price_reclaim_with_improved_stop" - else: - raise ValueError(f"Unknown re-entry policy: {self.name}") - - if reason is None: - return None - emitted = dict(candidate) - emitted["_reentry_reason"] = reason - self.emitted[reason] += 1 - return emitted - - def summary(self) -> dict: - return { - "daily_checks": self.checks, - "qualified_checks": self.gate_passes, - "emitted_by_reason": dict(self.emitted), - } - - -def _trade_summary(trades: list[dict]) -> dict: - reentries = [trade for trade in trades if trade.get("is_reentry")] - waits = [ - int(trade["reentry_wait_sessions"]) - for trade in reentries - if trade.get("reentry_wait_sessions") is not None - ] - return { - "transaction_cost": round( - sum(float(trade["transaction_cost"]) for trade in trades), 2 - ), - "reentry_trades": len(reentries), - "same_day_reentries": sum(wait == 0 for wait in waits), - "next_day_reentries": sum(wait == 1 for wait in waits), - "reentries_within_5_sessions": sum(wait <= 5 for wait in waits), - "avg_reentry_wait_sessions": round(sum(waits) / len(waits), 1) - if waits - else None, - "reentry_win_rate": round( - sum(float(trade["pnl"]) > 0 for trade in reentries) - / len(reentries) - * 100.0, - 1, - ) - if reentries - else None, - "reentry_total_pnl": round( - sum(float(trade["pnl"]) for trade in reentries), 2 - ), - } - - -async def _main() -> None: - args = _parse_args() - snapshot = Path(args.snapshot) - if not snapshot.exists(): - raise SystemExit(f"Snapshot not found: {snapshot}") - try: - start_date = date.fromisoformat(args.start_date) - except ValueError as exc: - raise SystemExit("--start-date must use YYYY-MM-DD") from exc - - os.environ["BACKTEST_SNAPSHOT_OFFLINE"] = "1" - os.environ["BACKTEST_ALLOW_SPAWN"] = "1" - - from app.models.ticker import Ticker - from app.services import backtest_service as bt - from app.services.admin_service import get_activation_config - from app.services.paper_trade_service import get_exit_policy - from app.services.recommendation_service import get_recommendation_config - - engine = create_async_engine(_sqlite_url(snapshot), pool_pre_ping=True) - Session = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False) - try: - async with Session() as db: - recommendation_config = await get_recommendation_config(db) - activation = await get_activation_config(db) - exit_config = await get_exit_policy(db) - benchmark_closes = await bt._load_benchmark_closes_for_backtest( - db, days=None, refresh=False - ) - ticker_result = await db.execute(select(Ticker).order_by(Ticker.symbol)) - symbols = [ticker.symbol for ticker in ticker_result.scalars().all()] - prices: dict[str, tuple] = {} - for index, symbol in enumerate(symbols, 1): - columns = await bt._fetch_columns(db, symbol) - if columns is not None: - prices[symbol] = columns - if not args.quiet and index % 50 == 0: - print(f"loaded prices: {index}/{len(symbols)}", flush=True) - finally: - await engine.dispose() - - cache_path = Path(args.candidate_cache) if args.candidate_cache else None - snapshot_stat = snapshot.stat() - cache_key = { - "snapshot": str(snapshot.resolve()), - "snapshot_size": snapshot_stat.st_size, - "snapshot_mtime_ns": snapshot_stat.st_mtime_ns, - "start_date": start_date.isoformat(), - } - candidates: list[dict] - if cache_path is not None and cache_path.exists(): - with cache_path.open("rb") as handle: - cached_replay = pickle.load(handle) # noqa: S301 - trusted local cache - if cached_replay.get("key") != cache_key: - raise SystemExit(f"Candidate cache does not match this run: {cache_path}") - candidates = list(cached_replay["candidates"]) - if not args.quiet: - print(f"loaded candidate cache: {cache_path}", flush=True) - else: - candidates = [] - workers = max(1, min(int(args.workers), multiprocessing.cpu_count() - 1)) - context = multiprocessing.get_context("spawn") - with ProcessPoolExecutor(max_workers=workers, mp_context=context) as pool: - futures = { - pool.submit( - bt._replay_candidates_for_period, - symbol, - columns, - recommendation_config, - activation, - benchmark_closes, - start_date, - ): symbol - for symbol, columns in prices.items() - } - for index, future in enumerate(as_completed(futures), 1): - candidates.extend(future.result()) - if not args.quiet and index % 25 == 0: - print(f"replayed tickers: {index}/{len(futures)}", flush=True) - if cache_path is not None: - cache_path.parent.mkdir(parents=True, exist_ok=True) - with cache_path.open("wb") as handle: - pickle.dump( - {"key": cache_key, "candidates": candidates}, - handle, - protocol=pickle.HIGHEST_PROTOCOL, - ) - if not args.quiet: - print(f"wrote candidate cache: {cache_path}", flush=True) - - bt._assign_momentum_percentiles(candidates) - bt._assign_residual_momentum_percentiles(candidates) - bt._assign_low_volatility_percentiles(candidates) - bt._assign_activation_momentum_percentiles(candidates) - bt._assign_residual_high_vol_blend(candidates) - threshold = float(activation.get("min_momentum_percentile", 80.0)) - for candidate in candidates: - candidate["qualified"] = bt._momentum_qualifies(candidate, threshold) - - strategy = next( - row for row in bt.PORTFOLIO_MONITOR_STRATEGIES if row.get("is_production") - ) - entry_config = bt._entry_variant_config(str(strategy["entry_variant"])) - if entry_config is None: - raise RuntimeError("Production entry configuration missing") - exit_policy = bt.LIVE_EXIT_MODE_TO_SIM.get( - str(exit_config.get("mode", "atr_trailing")), "atr_trail3" - ) - hold_days = int(exit_config.get("hold_days", max(bt.TIME_EXIT_DAYS))) - trail_multiplier = float( - exit_config.get("atr_multiplier", bt.ATR_TRAIL_MULTIPLIER) - ) - sim_kwargs = { - "ranking_key": str( - entry_config.get("ranking_key") or entry_config["percentile_key"] - ), - "max_positions": int(entry_config["max_positions"]), - "risk_per_trade": float(entry_config["risk_per_trade"]), - "atr_trail_multiplier": trail_multiplier, - "start_date": start_date, - "include_trades": True, - } - - daily_engine = DailySetupEngine( - prices, recommendation_config, activation, benchmark_closes - ) - if args.cooldowns is None: - policy_names = ( - "immediate", - "cooldown_5", - "gate_reset", - "gate_reset_or_reclaim", - ) - else: - cooldowns = sorted(set(args.cooldowns)) - if any(value < 1 for value in cooldowns): - raise SystemExit("--cooldowns values must be positive integers") - policy_names = ("immediate", *(f"cooldown_{value}" for value in cooldowns)) - - arms: list[dict] = [] - for policy_name in policy_names: - policy = ReentryPolicy(policy_name, daily_engine) - sim = bt._simulate_portfolio( - candidates, - prices, - benchmark_closes, - exit_policy, - hold_days, - post_stop_reentry_fn=policy, - **sim_kwargs, - ) - if sim is None: - raise RuntimeError(f"Policy {policy_name} produced no trades") - trades = list(sim.pop("trade_details")) - arms.append({ - "arm": policy_name, - **sim, - "turnover": _trade_summary(trades), - "policy": policy.summary(), - "trade_details": trades, - }) - - output = Path(args.out) if args.out else _default_output_path() - report = { - "generated_at": datetime.now().astimezone().isoformat(), - "snapshot": str(snapshot.resolve()), - "period_start": start_date.isoformat(), - "tickers": len(prices), - "entry_candidates": len(candidates), - "qualified_candidates": sum(bool(row["qualified"]) for row in candidates), - "params": { - "initial_entry_cadence_days": bt.STEP_DAYS, - "post_stop_evaluation_cadence_days": 1, - "setup_stop_atr_multiplier": bt.ATR_MULTIPLIER, - "exit_policy": exit_policy, - "exit_atr_multiplier": trail_multiplier, - "hold_days": hold_days, - "cost_per_side_pct": bt.COST_PER_SIDE * 100.0, - "momentum_percentile_floor": threshold, - "reclaim_atr_buffer": RECLAIM_ATR_BUFFER, - "cooldown_sessions": cooldowns if args.cooldowns is not None else None, - }, - "arms": arms, - "note": ( - "Initial opportunities retain the validated weekly replay cadence. " - "Only tickers stopped at their initial stop switch to daily evaluation, " - "which isolates next-day/same-episode re-entry churn. A cooldown of N " - "sessions permits the first re-entry at wait_sessions=N. Gate reset " - "requires at least one unqualified daily close before requalification. " - "The reclaim arm alternatively accepts a close above stop-day high + " - "0.25 ATR only when the new setup stop is above the prior stop." - ), - } - output.parent.mkdir(parents=True, exist_ok=True) - output.write_text(json.dumps(report, indent=2) + "\n", encoding="utf-8") - - print(f"Report written: {output}") - for arm in arms: - turnover = arm["turnover"] - print( - f"{arm['arm']}: Sharpe {arm['sharpe']}, CAGR {arm['cagr_pct']}%, " - f"DD {arm['max_drawdown_pct']}%, trades {arm['trades']}, " - f"reentries {turnover['reentry_trades']}, fees ${turnover['transaction_cost']}" - ) - - -if __name__ == "__main__": - asyncio.run(_main())