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Pigbibi merged 1 commit into from
Sep 1, 2026
Merged

Require closed research evidence for promotion #224

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62 changes: 40 additions & 22 deletions scripts/research_cn_dividend_quality_snapshot_proxy_backtest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,10 @@
ProxyBacktestResult,
compute_backtest_metrics,
)
from cn_equity_strategies.backtest.promotion_gate import ( # noqa: E402
attach_research_evidence,
build_research_evidence,
)
from cn_equity_strategies.strategies import cn_dividend_quality_snapshot as dividend_strategy # noqa: E402
from cn_equity_strategies.strategies.etf_rotation_core import normalize_symbol # noqa: E402

Expand Down Expand Up @@ -89,6 +93,17 @@ def pipeline_normalize_symbol(symbol: Any) -> str:
CACHE_DIR = ROOT / ".cache" / "cn_equity_strategies"
CACHE_VERSION = "v1"

DIVIDEND_SNAPSHOT_RESEARCH_EVIDENCE = build_research_evidence(
research_only=True,
promotion_eligible=False,
point_in_time=False,
historical_membership_complete=False,
historical_constituents_complete=False,
adjustment_provenance_complete=False,
universe_provenance_complete=False,
survivorship_bias_controlled=False,
)


def _cache_path(prefix: str, *, parts: tuple[str, ...]) -> Path:
digest = hashlib.sha1("|".join([CACHE_VERSION, prefix, *parts]).encode("utf-8")).hexdigest()[:16]
Expand Down Expand Up @@ -738,29 +753,32 @@ def main() -> None:
"2021_2022": ("2021-01-01", "2022-12-31"),
"2023_2026": ("2023-01-01", args.end),
}
output = {
"profile": dividend_strategy.PROFILE_NAME,
"start": args.start,
"end": args.end,
"universe": list(universe),
"universe_mode": args.universe_mode,
"panel_diagnostics": panel_diag,
"strategy_full": strategy.metrics,
"benchmark_510300_full": benchmark.metrics,
"periods": {
key: {
"dividend_quality": _metrics_slice(strategy.daily_returns, pstart, pend),
"benchmark_510300": _metrics_slice(benchmark.daily_returns, pstart, pend),
}
for key, (pstart, pend) in periods.items()
output = attach_research_evidence(
{
"profile": dividend_strategy.PROFILE_NAME,
"start": args.start,
"end": args.end,
"universe": list(universe),
"universe_mode": args.universe_mode,
"panel_diagnostics": panel_diag,
"strategy_full": strategy.metrics,
"benchmark_510300_full": benchmark.metrics,
"periods": {
key: {
"dividend_quality": _metrics_slice(strategy.daily_returns, pstart, pend),
"benchmark_510300": _metrics_slice(benchmark.daily_returns, pstart, pend),
}
for key, (pstart, pend) in periods.items()
},
"limitations": [
f"universe_mode={args.universe_mode}; expanded pool uses fhps dividend-yield filter, not full A-share",
"fhps table uses latest available report table, not fully point-in-time report selection",
"proxy uses 510300 calendar + per-symbol ffill; monthly panel filters symbols with price history at as_of",
"evidence gate only; not promotion-ready without PIT fhps and live data validation",
],
},
"limitations": [
f"universe_mode={args.universe_mode}; expanded pool uses fhps dividend-yield filter, not full A-share",
"fhps table uses latest available report table, not fully point-in-time report selection",
"proxy uses 510300 calendar + per-symbol ffill; monthly panel filters symbols with price history at as_of",
"evidence gate only; not promotion-ready without PIT fhps and live data validation",
],
}
research_evidence=DIVIDEND_SNAPSHOT_RESEARCH_EVIDENCE,
)

print("\n========== P3.5 cn_dividend_quality_snapshot proxy ==========")
print(
Expand Down
44 changes: 33 additions & 11 deletions scripts/research_cn_industry_etf_rotation_aggressive_matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,11 @@
sys.path.insert(0, candidate_str)

from cn_equity_strategies.backtest.proxy_simulator import ProxyBacktestConfig, run_proxy_backtest # noqa: E402
from cn_equity_strategies.backtest.promotion_gate import evaluate_promotion # noqa: E402
from cn_equity_strategies.backtest.promotion_gate import ( # noqa: E402
attach_research_evidence,
build_research_evidence,
evaluate_promotion,
)
from cn_equity_strategies.strategies import cn_industry_etf_rotation as industry_rotation # noqa: E402
from cn_equity_strategies.strategies.industry_etf_rotation_presets import ( # noqa: E402
AGGRESSIVE_RESEARCH_PRESETS,
Expand All @@ -33,6 +37,17 @@
_period_metrics,
)

INDUSTRY_ETF_RESEARCH_EVIDENCE = build_research_evidence(
research_only=True,
promotion_eligible=False,
point_in_time=False,
historical_membership_complete=False,
historical_constituents_complete=False,
adjustment_provenance_complete=False,
universe_provenance_complete=False,
survivorship_bias_controlled=False,
)


def _run_preset(market_history, key: str, preset: dict[str, Any]) -> dict[str, Any]:
rebalance_frequency = str(preset.get("rebalance_frequency") or "monthly")
Expand Down Expand Up @@ -92,16 +107,23 @@ def run_matrix(*, start: str, end: str, suite: str = "etf") -> dict[str, Any]:
market_history = _download_market_history(start=download_start, end=end)
presets = {"conservative_v1": CONSERVATIVE_V1_PRESET, **AGGRESSIVE_RESEARCH_PRESETS}
results = {key: _run_preset(market_history, key, preset) for key, preset in presets.items()}
promotion = evaluate_promotion(results, PROMOTION_GATE)
return {
"start": start,
"end": end,
"suite": suite,
"status": "research_backtest_only",
"conservative_baseline": "conservative_v1",
"variants": results,
"promotion_review": promotion,
}
promotion = evaluate_promotion(
results,
PROMOTION_GATE,
research_evidence=INDUSTRY_ETF_RESEARCH_EVIDENCE,
)
return attach_research_evidence(
{
"start": start,
"end": end,
"suite": suite,
"status": "research_backtest_only",
"conservative_baseline": "conservative_v1",
"variants": results,
"promotion_review": promotion,
},
research_evidence=INDUSTRY_ETF_RESEARCH_EVIDENCE,
)


def _print_report(payload: dict[str, Any]) -> None:
Expand Down
57 changes: 38 additions & 19 deletions scripts/research_cn_momentum_stock_rotation_proxy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,11 @@
if candidate.exists() and candidate_str not in sys.path:
sys.path.insert(0, candidate_str)

from cn_equity_strategies.backtest.promotion_gate import evaluate_promotion # noqa: E402
from cn_equity_strategies.backtest.promotion_gate import ( # noqa: E402
attach_research_evidence,
build_research_evidence,
evaluate_promotion,
)
from cn_equity_strategies.research.momentum_stock_history import ( # noqa: E402
BENCHMARK_SYMBOL,
active_stock_symbols_at_start,
Expand All @@ -40,6 +44,17 @@

ResearchTrack = Literal["momentum", "thematic", "both"]

MOMENTUM_STOCK_RESEARCH_EVIDENCE = build_research_evidence(
research_only=True,
promotion_eligible=False,
point_in_time=False,
historical_membership_complete=False,
historical_constituents_complete=False,
adjustment_provenance_complete=False,
universe_provenance_complete=False,
survivorship_bias_controlled=False,
)


def _extra_symbols_for_preset(preset: dict[str, Any]) -> tuple[str, ...]:
extras: list[str] = []
Expand Down Expand Up @@ -166,26 +181,30 @@ def run_momentum_stock_matrix(
promotion = evaluate_promotion(
{"conservative_v1": conservative, **results},
STOCK_MOMENTUM_PROMOTION_GATE,
research_evidence=MOMENTUM_STOCK_RESEARCH_EVIDENCE,
)

return {
"start": start,
"end": end,
"track": "cross_section_momentum_riskoff" if suite == "csi500_riskoff" else "cross_section_momentum",
"status": "research_backtest_only",
"default_universe_mode": suite or universe_mode or "all_presets",
"conservative_etf_baseline": conservative,
"variants": results,
"promotion_review": promotion,
"promotion_gate": STOCK_MOMENTUM_PROMOTION_GATE,
"universe_diagnostics": universe_diagnostics,
"limitations": [
"index constituents (CSI500/1000) use latest csindex table — not fully point-in-time",
"liquid_top uses current spot turnover snapshot — not historical liquidity PIT",
"selection is cross-sectional momentum within broad pool, not fixed thematic industry list",
"not runtime-enabled; compare vs ETF conservative_v1 and thematic 8-name sleeve separately",
],
}
return attach_research_evidence(
{
"start": start,
"end": end,
"track": "cross_section_momentum_riskoff" if suite == "csi500_riskoff" else "cross_section_momentum",
"status": "research_backtest_only",
"default_universe_mode": suite or universe_mode or "all_presets",
"conservative_etf_baseline": conservative,
"variants": results,
"promotion_review": promotion,
"promotion_gate": STOCK_MOMENTUM_PROMOTION_GATE,
"universe_diagnostics": universe_diagnostics,
"limitations": [
"index constituents (CSI500/1000) use latest csindex table — not fully point-in-time",
"liquid_top uses current spot turnover snapshot — not historical liquidity PIT",
"selection is cross-sectional momentum within broad pool, not fixed thematic industry list",
"not runtime-enabled; compare vs ETF conservative_v1 and thematic 8-name sleeve separately",
],
},
research_evidence=MOMENTUM_STOCK_RESEARCH_EVIDENCE,
)


def run_thematic_reference(*, start: str, end: str) -> dict[str, Any]:
Expand Down
57 changes: 38 additions & 19 deletions scripts/research_cn_thematic_stock_rotation_proxy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,11 @@
if candidate.exists() and candidate_str not in sys.path:
sys.path.insert(0, candidate_str)

from cn_equity_strategies.backtest.promotion_gate import evaluate_promotion # noqa: E402
from cn_equity_strategies.backtest.promotion_gate import ( # noqa: E402
attach_research_evidence,
build_research_evidence,
evaluate_promotion,
)
from cn_equity_strategies.strategies.industry_etf_rotation_presets import ( # noqa: E402
CONSERVATIVE_V1_PRESET,
OPTICAL_COMPUTE_STOCK_SYMBOLS,
Expand All @@ -37,6 +41,17 @@

_ETF_SYMBOL_PREFIXES = ("51", "15", "58")

THEMATIC_STOCK_RESEARCH_EVIDENCE = build_research_evidence(
research_only=True,
promotion_eligible=False,
point_in_time=False,
historical_membership_complete=False,
historical_constituents_complete=False,
adjustment_provenance_complete=False,
universe_provenance_complete=False,
survivorship_bias_controlled=False,
)


def _is_etf_symbol(symbol: str) -> bool:
normalized = str(symbol).strip()
Expand Down Expand Up @@ -173,26 +188,30 @@ def _preset_universe(preset: dict[str, Any]) -> tuple[str, ...]:
promotion = evaluate_promotion(
{"conservative_v1": conservative, **results},
STOCK_THEMATIC_PROMOTION_GATE,
research_evidence=THEMATIC_STOCK_RESEARCH_EVIDENCE,
)

return {
"start": start,
"end": end,
"suite": suite,
"status": "research_backtest_only",
"active_symbols": list(active),
"candidate_symbols": list(OPTICAL_COMPUTE_STOCK_SYMBOLS),
"conservative_etf_baseline": conservative,
"variants": results,
"promotion_review": promotion,
"promotion_gate": STOCK_THEMATIC_PROMOTION_GATE,
"limitations": [
"fixed optical/compute stock list (survivorship / theme hindsight)",
"requires overlapping listing history; universe shrinks to active names at start",
"not runtime-enabled; stricter gate vs ETF conservative_v1",
"risk presets may include ETF benchmark symbols (510300/512760) for risk-off",
],
}
return attach_research_evidence(
{
"start": start,
"end": end,
"suite": suite,
"status": "research_backtest_only",
"active_symbols": list(active),
"candidate_symbols": list(OPTICAL_COMPUTE_STOCK_SYMBOLS),
"conservative_etf_baseline": conservative,
"variants": results,
"promotion_review": promotion,
"promotion_gate": STOCK_THEMATIC_PROMOTION_GATE,
"limitations": [
"fixed optical/compute stock list (survivorship / theme hindsight)",
"requires overlapping listing history; universe shrinks to active names at start",
"not runtime-enabled; stricter gate vs ETF conservative_v1",
"risk presets may include ETF benchmark symbols (510300/512760) for risk-off",
],
},
research_evidence=THEMATIC_STOCK_RESEARCH_EVIDENCE,
)


def _print_report(payload: dict[str, Any]) -> None:
Expand Down
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