finish experiment 42 (exp/42-q10-hmm-regime-overlay-entry-gate-on-sph)

code/MANIFEST.txt

@@ -1,5 +1,5 @@
 # TradeAC custom-qlib-code snapshot (auto-generated)
-# parent repo HEAD : 507846cee16eeee11daf33c4176e8aec79b985b2
+# parent repo HEAD : 22a57a81c62aa2d99f9362a50b52fb4c0d82d1c2
 #   tac-qlib/tac_qlib/contrib
 #   tac-qlib/tac_qlib/data
 # per-file hashes (git hash-object):

evidence/q08-risklimit/RESULT.md

@@ -1,35 +0,0 @@
-# Q08 — Risk-limit A/B re-validation (trace 40)
-
-**Status:** DONE (verdict: REFUTED as an IR edge; safety-net value retained)
-
-## Input
-- Reference signal: exp-26 pred, run `21afc6afdb674a399b59dd76c97628ce` (mlflow exp 25)
-- Window: 2026-01-04 → 2026-08-10, Topk10 n_drop1, SPY benchmark, $1M, 5/15bp/$5
-- Tool: `rd_risk_calibrate` (A/B + sensitivity grid). Full JSON: `risk_calibration.json`
-
-## Candidate spec (round-3 live spec)
-`{"liquidity_floor_adv": 5000000, "size_cap_pct": 0.12, "concentration_cap_pct": 0.95, "drawdown_pause_pct": 0.10}`
-
-## Results (net, with cost)
-| Config | IR | Ann. return | Max DD |
-|---|---|---|---|
-| baseline (no limits) | 1.5804 | +27.50% | −6.91% |
-| **candidate (5M floor + caps)** | **1.5121** | +2.20% | **−0.65%** |
-| liquidity $10M | 1.5457 | +2.25% | −0.64% |
-
-## Findings
-- **Floor binds, not a no-op**: $5M liquidity floor dropped 8 symbols —
-  `DBA, DBC, ESPO, FDN, REM, TAN, UNG, XAR`.
-- **No IR edge from the gate**: candidate IR (1.512) is BELOW baseline (1.580).
-  The exp-18 direction (floor IR 0.81→0.98) does NOT reproduce on the clean-lake
-  reference signal.
-- **Drawdown cut is pure defunding**: size_cap 0.12 × concentration 0.95 fold
-  the effective risk_degree to ~0.0095 → ~$9.5k deployed of $1M (~100x less).
-  Sensitivity grid shows both caps are no-ops (conc 20–50% identical,
-  size_cap 5–20% identical); only the liquidity floor moves returns, marginally.
-- **Conclusion**: keep the live spec as a safety net; there is no risk-limit
-  gate IR edge to harvest when the signal is the bottleneck (exp-20 pattern).
-
-## Artifacts on this branch
-- `evidence/q08-risklimit/risk_calibration.json` — full calibration dump
-- `queue/designs/q08_risk_limit_ab.md` — the pre-registered design doc

evidence/q08-risklimit/risk_calibration.json

@@ -1,401 +0,0 @@
-{
-  "rows": [
-    {
-      "label": "baseline (no limits)",
-      "mean": 0.001155,
-      "std": 0.011279,
-      "annualized_return": 0.274989,
-      "information_ratio": 1.580427,
-      "max_drawdown": -0.069145
-    },
-    {
-      "label": "liquidity $10,000,000",
-      "mean": 9.4e-05,
-      "std": 0.000942,
-      "annualized_return": 0.022464,
-      "information_ratio": 1.545736,
-      "max_drawdown": -0.006389
-    },
-    {
-      "label": "conc 20%",
-      "mean": 0.000115,
-      "std": 0.001168,
-      "annualized_return": 0.027285,
-      "information_ratio": 1.513718,
-      "max_drawdown": -0.008104
-    },
-    {
-      "label": "conc 30%",
-      "mean": 0.000115,
-      "std": 0.001168,
-      "annualized_return": 0.027285,
-      "information_ratio": 1.513718,
-      "max_drawdown": -0.008104
-    },
-    {
-      "label": "conc 40%",
-      "mean": 0.000115,
-      "std": 0.001168,
-      "annualized_return": 0.027285,
-      "information_ratio": 1.513718,
-      "max_drawdown": -0.008104
-    },
-    {
-      "label": "conc 50%",
-      "mean": 0.000115,
-      "std": 0.001168,
-      "annualized_return": 0.027285,
-      "information_ratio": 1.513718,
-      "max_drawdown": -0.008104
-    },
-    {
-      "label": "candidate {\"liquidity_floor_adv\": 5000000.0, \"size_cap_pct\": 0.12, \"concentration_cap_pct\": 0.95, \"drawdown_pause_pct\": 0.1}",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "size_cap 5%",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "size_cap 10%",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "size_cap 15%",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "size_cap 20%",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "liquidity $5,000,000",
-      "mean": 9.2e-05,
-      "std": 0.000943,
-      "annualized_return": 0.021991,
-      "information_ratio": 1.512051,
-      "max_drawdown": -0.00653
-    },
-    {
-      "label": "liquidity $1,000,000",
-      "mean": 9.1e-05,
-      "std": 0.000929,
-      "annualized_return": 0.021625,
-      "information_ratio": 1.508748,
-      "max_drawdown": -0.006376
-    },
-    {
-      "label": "liquidity $2,500,000",
-      "mean": 7.1e-05,
-      "std": 0.000918,
-      "annualized_return": 0.017,
-      "information_ratio": 1.199721,
-      "max_drawdown": -0.007158
-    }
-  ],
-  "runs": {
-    "baseline": {
-      "risk": {
-        "mean": 0.0011554172081987572,
-        "std": 0.01127853762493476,
-        "annualized_return": 0.27498929555130425,
-        "information_ratio": 1.5804272791471323,
-        "max_drawdown": -0.06914515336341577
-      },
-      "applied": {}
-    },
-    "candidate": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "size_cap 5%": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "size_cap 10%": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "size_cap 15%": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "size_cap 20%": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "conc 20%": {
-      "risk": {
-        "mean": 0.00011464156491316718,
-        "std": 0.0011683839517000441,
-        "annualized_return": 0.027284692449333788,
-        "information_ratio": 1.5137180903503433,
-        "max_drawdown": -0.008103887185240407
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "conc 30%": {
-      "risk": {
-        "mean": 0.00011464156491316718,
-        "std": 0.0011683839517000441,
-        "annualized_return": 0.027284692449333788,
-        "information_ratio": 1.5137180903503433,
-        "max_drawdown": -0.008103887185240407
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "conc 40%": {
-      "risk": {
-        "mean": 0.00011464156491316718,
-        "std": 0.0011683839517000441,
-        "annualized_return": 0.027284692449333788,
-        "information_ratio": 1.5137180903503433,
-        "max_drawdown": -0.008103887185240407
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "conc 50%": {
-      "risk": {
-        "mean": 0.00011464156491316718,
-        "std": 0.0011683839517000441,
-        "annualized_return": 0.027284692449333788,
-        "information_ratio": 1.5137180903503433,
-        "max_drawdown": -0.008103887185240407
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "liquidity $1,000,000": {
-      "risk": {
-        "mean": 9.086210454881382e-05,
-        "std": 0.0009290831160004576,
-        "annualized_return": 0.021625180882617688,
-        "information_ratio": 1.508747982736451,
-        "max_drawdown": -0.006376134679664126
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "ESPO"
-        ]
-      }
-    },
-    "liquidity $2,500,000": {
-      "risk": {
-        "mean": 7.142665167642606e-05,
-        "std": 0.0009184775632266332,
-        "annualized_return": 0.016999543098989402,
-        "information_ratio": 1.1997208834083914,
-        "max_drawdown": -0.0071582979845040825
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "REM",
-          "XAR"
-        ]
-      }
-    },
-    "liquidity $5,000,000": {
-      "risk": {
-        "mean": 9.239707947451976e-05,
-        "std": 0.0009427144352738658,
-        "annualized_return": 0.0219905049149357,
-        "information_ratio": 1.5120514373488407,
-        "max_drawdown": -0.006530482262119444
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "REM",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    },
-    "liquidity $10,000,000": {
-      "risk": {
-        "mean": 9.438545151345752e-05,
-        "std": 0.0009420158170657147,
-        "annualized_return": 0.02246373746020289,
-        "information_ratio": 1.5457360696934006,
-        "max_drawdown": -0.006388809561209335
-      },
-      "applied": {
-        "dropped_liquidity": [
-          "DBA",
-          "DBC",
-          "ESPO",
-          "FDN",
-          "ICLN",
-          "ITA",
-          "MDY",
-          "REM",
-          "SHY",
-          "TAN",
-          "UNG",
-          "XAR"
-        ]
-      }
-    }
-  },
-  "candidate": {
-    "liquidity_floor_adv": 5000000.0,
-    "size_cap_pct": 0.12,
-    "concentration_cap_pct": 0.95,
-    "drawdown_pause_pct": 0.1
-  }
-}

queue/designs/q08_risk_limit_ab.md

@@ -1,34 +0,0 @@
-# QUEUE-08 — Risk-limit A/B re-validation: $5M liquidity floor on the exp-26 reference
-
-**Status:** QUEUED · **Priority:** P1 · **Effort:** tool-only (no new code)
-
-## Hypothesis (prove)
-The $5M liquidity floor improves net IR and cuts drawdown on the **post-reset**
-reference signal (pre-reset exp 18, EVIDENCE#008: net IR 0.81→0.98, cumDD
-7.93%→5.44%), while size/concentration caps hurt by cutting deployed capital.
-Needs re-validation on the exp-26 lineage because exp 18 is pre-clean-lake and
-not comparable (EVIDENCE#009/010). Source: `book/CLAIMS.md` open question +
-`book/README.md` `TODO(evidence-needed: reconciliation of exp 18 risk-limit spec
-on the post-reset reference signal)`.
-
-## Change vs exp-26 reference (ONE variable)
-- Reference: the saved exp-26 prediction (run `21afc6af…`, mlflow exp 25).
-- A/B via `rd_risk_calibrate` (runs limit-vs-no-limit A/B + sensitivity grid
-  over size_cap_pct, concentration_cap_pct, liquidity_floor_adv) and/or
-  `rd_backtest` with `risk_limits` on the SAME saved `pred.pkl`:
-  - baseline: no limits (this must reproduce the exp-26 net +2.13% / IR 0.21);
-  - candidate: `{"liquidity_floor_adv": 5000000, "size_cap_pct": 0.12,
-    "concentration_cap_pct": 0.95, "drawdown_pause_pct": 0.10}` (round-3 spec).
-- Pick the spec (B2 calibration) that keeps live ≈ backtest.
-
-## Acceptance
-- Candidate spec: `net_IR > 0.21` AND `net_max_drawdown < 7.69%` vs no-limit on
-  the same pred. Size/concentration caps expected to REDUCE deployed capital
-  (record the direction as confirmation of exp 18).
-- If the floor is a no-op (gates don't bind at this signal) → report that gates
-  are no-ops when the signal is the bottleneck (exp 20 pattern) as a PROVEN
-  clean-lake result.
-
-## Execution prerequisites
-- None (uses saved pred + `rd_risk_calibrate`/`rd_backtest`). Trace the A/B as
-  an experiment; record the spec chosen for the next live round.

queue/workflows/q10_regime.yaml

@@ -0,0 +1,144 @@
+# QUEUE-me
+# HMM regime overlay (Q10): identical TopkDropout selection, entry gated on sp_hmm_p_regime1 >= 0.5.
+# Acceptance: net_max_drawdown < 7.69% AND net_IR >= 0.21. No regime column enters feature_fields.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set FEATURES = "$open,$high,$low,$close,$vwap,$volume,sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-q10-regime"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-10
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "{{ FEATURES }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: RegimeGateDropoutStrategy
+                      module_path: tac_qlib.contrib.strategy.regime_gate
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 1
+                          only_tradable: true
+                          risk_degree: 0.95
+                          regime_threshold: 0.5
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r0_5seed_baseline.yaml

@@ -0,0 +1,135 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: TopkDropoutStrategy
+                      module_path: qlib.contrib.strategy
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r0_det_baseline.yaml

@@ -0,0 +1,135 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 1
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: TopkDropoutStrategy
+                      module_path: qlib.contrib.strategy
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r1_2seed.yaml

@@ -0,0 +1,135 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7"
+            parallel: 2
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: TopkDropoutStrategy
+                      module_path: qlib.contrib.strategy
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r2_momentum.yaml

@@ -0,0 +1,136 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: MomentumGateTopk
+                      module_path: tac_qlib.contrib.strategy.momentum_gate
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          min_momentum: 0.0
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r3_hmm_risk.yaml

@@ -0,0 +1,138 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: HmmRiskTopk
+                      module_path: tac_qlib.contrib.strategy.hmm_risk
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          hmm_pause_pct: 0.70
+                          drawdown_pause_pct: 8.0
+                          liquidity_floor_adv: 5000000
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r4_rolling_ic.yaml

@@ -0,0 +1,137 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            weight_mode: rolling_ic
+            rolling_ic_window: 21
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: TopkDropoutStrategy
+                      module_path: qlib.contrib.strategy
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d

workflows/exp20-risk-limit-improve/r5_ma3_ewma.yaml

@@ -0,0 +1,135 @@
+# -----------------------------------------------------------------------------
+# EXP 20 - R1: 2-seed ensemble (seeds 42,7), TopkDropout baseline.
+#
+# Runtime cut: 2 seeds instead of 5. Everything else identical to the reference
+# (test 2026-01-04..2026-08-10, SPY, costs 5bp/15bp). Measures whether the
+# 2-seed ensemble keeps the reference quality at ~2/5 the training time.
+#
+# Run:
+#   rd_run_workflow config_path=experiments/workflows/exp20-risk-limit-improve/r1_2seed.yaml \
+#       experiment_name=tac-rd-risk-limit
+# -----------------------------------------------------------------------------
+{%- set LAKE = TAC_LAKE_DIR %}
+{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
+{%- set SP_FIELDS = "sp_ret,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead,sma_3,ema_3" %}
+
+qlib_init:
+    provider_uri: "{{ LAKE }}"
+    region: us
+    expression_cache: null
+    dataset_cache: null
+
+    calendar_provider:
+        class: tac_qlib.data.providers.LakeCalendarProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+    instrument_provider:
+        class: tac_qlib.data.providers.LakeInstrumentProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+            markets: {}
+    feature_provider:
+        class: tac_qlib.data.providers.LakeFeatureProvider
+        kwargs:
+            lake_root: "{{ LAKE }}"
+            market: US
+
+    exp_manager:
+        class: MLflowExpManager
+        module_path: qlib.workflow.expm
+        kwargs:
+            uri: "sqlite:///{{ LAKE }}/mlruns.db"
+            default_exp_name: "tac-rd-risk-limit"
+
+task:
+    model:
+        class: RankICEnsembleLGBModel
+        module_path: tac_qlib.contrib.model.rank_ensemble
+        kwargs:
+            loss: mse
+            learning_rate: 0.02
+            num_leaves: 31
+            n_estimators: 3000
+            num_boost_round: 3000
+            early_stopping_rounds: 200
+            min_data_in_leaf: 20
+            lambda_l2: 0.5
+            colsample_bytree: 0.8
+            subsample: 0.8
+            subsample_freq: 1
+            reg_alpha: 0.1
+            reg_lambda: 1.0
+            seeds: "42,7,2026,99,123"
+            parallel: 5
+
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: TACHandler
+                module_path: tac_qlib.contrib.data.handler
+                kwargs:
+                    instruments: "{{ UNIVERSE }}"
+                    start_time: 2015-01-03
+                    end_time: 2026-08-14
+                    fit_start_time: 2016-01-04
+                    fit_end_time: 2025-09-01
+                    freq: day
+                    lake_root: "{{ LAKE }}"
+                    market: US
+                    label: "Ref($close,-6)/Ref($close,-1)-1"
+                    feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
+                    infer_processors:
+                        - class: DropAllNaN
+                          kwargs: {}
+                        - class: ProcessInf
+                          kwargs: {}
+                        - class: CSRankNorm
+                          kwargs: {}
+                        - class: ZScoreNorm
+                          kwargs: {}
+                        - class: Fillna
+                          kwargs: {}
+            segments:
+                train: [2016-01-04, 2025-09-01]
+                valid: [2025-09-03, 2026-01-03]
+                test: [2026-01-04, 2026-08-10]
+
+    record:
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              ana_long_short: true
+              ann_scaler: 252
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs:
+              config:
+                  strategy:
+                      class: TopkDropoutStrategy
+                      module_path: qlib.contrib.strategy
+                      kwargs:
+                          signal: "<PRED>"
+                          topk: 10
+                          n_drop: 2
+                          only_tradable: true
+                          risk_degree: 0.95
+                  backtest:
+                      start_time: 2026-01-04
+                      end_time: 2026-08-10
+                      account: 1000000
+                      benchmark: SPY
+                      exchange_kwargs:
+                          codes: "{{ UNIVERSE }}"
+                          deal_price: $close
+                          freq: day
+                          open_cost: 0.0005
+                          close_cost: 0.0015
+                          min_cost: 5.0
+              risk_analysis_freq: 1d