Align backtest production sim with live runtime config
The portfolio monitor's Production row now replays the live qualification flag and the Admin exit policy (mode/ATR multiplier/hold days) instead of a frozen research-variant gate, so Admin tuning is reflected in the next run. Single-source the 80/20 strategy_rank weights in momentum_service and pin every dual-defined constant with a parity test. Behavior-preserving today: the production sim reproduces the README baseline exactly. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Claude Fable 5
@@ -44,7 +44,10 @@ from app.models.ticker import Ticker
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from app.services import settings_store
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from app.services.admin_service import get_activation_config, update_setting
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from app.services.indicator_service import _extract_ohlcv, compute_atr
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from app.services.momentum_service import compute_realized_vol_6m
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from app.services.momentum_service import (
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STRATEGY_RANK_MOMENTUM_WEIGHT,
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compute_realized_vol_6m,
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)
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from app.services.outcome_service import (
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OUTCOME_AMBIGUOUS,
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OUTCOME_STOP_HIT,
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@@ -941,7 +944,9 @@ def _assign_residual_high_vol_blend(candidates: list[dict]) -> None:
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"""Research ranks: residual momentum blended with higher-vol preference."""
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for output_key, residual_weight in (
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(RESIDUAL_HIGH_VOL_BLEND_90_10_KEY, 0.9),
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(RESIDUAL_HIGH_VOL_BLEND_80_20_KEY, 0.8),
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# The production ordering weight comes from momentum_service so the
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# simulated production rank cannot drift from the live strategy_rank.
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(RESIDUAL_HIGH_VOL_BLEND_80_20_KEY, STRATEGY_RANK_MOMENTUM_WEIGHT),
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(RESIDUAL_HIGH_VOL_BLEND_KEY, 0.7),
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(RESIDUAL_HIGH_VOL_BLEND_60_40_KEY, 0.6),
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):
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@@ -1061,6 +1066,20 @@ SIM_STARTING_CAPITAL = 10_000.0
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SIM_MAX_POSITIONS = 10
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SIM_RISK_PER_TRADE = 0.01 # fraction of equity risked per position (entry→stop)
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SIM_NOTIONAL_CAP = 0.20 # max fraction of equity per position (no margin)
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# The "atr_trail3" research policy's trail width. Must equal the live default
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# (paper_trade_service.DEFAULT_ATR_MULTIPLIER) — enforced by the parity test.
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# The production portfolio-monitor row additionally follows the *runtime* Admin
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# exit policy, so tuning it live is reflected in the next backtest run.
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ATR_TRAIL_MULTIPLIER = 3.0
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# How live Admin exit modes map onto simulator exit policies. "trailing"
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# (percent trail) has no simulator counterpart and falls back to the plain
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# hold-to-horizon book; the row's live_exit_mode field keeps that visible.
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LIVE_EXIT_MODE_TO_SIM = {
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"atr_trailing": "atr_trail3",
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"time": "hold",
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"target": "target",
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"trailing": "hold",
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}
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def _simulate_portfolio(
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@@ -1074,6 +1093,7 @@ def _simulate_portfolio(
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ranking_key: str = PRODUCTION_PERCENTILE_KEY,
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max_positions: int = SIM_MAX_POSITIONS,
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risk_per_trade: float = SIM_RISK_PER_TRADE,
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atr_trail_multiplier: float = ATR_TRAIL_MULTIPLIER,
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start_date: date | None = None,
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include_curve: bool = False,
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) -> dict | None:
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@@ -1249,7 +1269,7 @@ def _simulate_portfolio(
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pos["highest_close"] = max(pos["highest_close"], bar.close)
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atr = _atr(sym, bar.idx)
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if atr is not None:
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next_stop = pos["highest_close"] - 3.0 * atr
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next_stop = pos["highest_close"] - atr_trail_multiplier * atr
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if next_stop < bar.close:
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pos["stop"] = max(pos["stop"], next_stop)
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@@ -1756,9 +1776,16 @@ PORTFOLIO_MONITOR_STRATEGIES: tuple[dict, ...] = (
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{
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"strategy": PRODUCTION_PORTFOLIO_STRATEGY,
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"label": "Production: residual/high-vol 80/20 + 3x ATR trail",
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"description": "Residual gate, 80/20 residual/high-vol rank, 3x ATR trailing stop.",
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"description": (
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"The live strategy: production activation gate and Admin exit policy "
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"as currently configured, 80/20 residual/high-vol rank."
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),
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"entry_variant": "residual80_highvol_blend80_20_fixed10",
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"exit_policy": "atr_trail3",
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# The production row replays what the platform actually does right now:
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# the live qualification flag (runtime Admin activation settings) and the
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# live Admin exit policy, instead of the frozen research-variant gate.
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"use_live_config": True,
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"is_production": True,
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},
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)
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@@ -1817,6 +1844,7 @@ def _portfolio_monitor(
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prices: dict[str, tuple],
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_spy_closes: dict[date, float] | None,
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hold_days: int,
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live_exit_policy: dict | None = None,
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) -> dict:
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latest_ord = max((max(cols[0]) for cols in prices.values() if cols[0]), default=None)
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rows: list[dict] = []
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@@ -1825,18 +1853,40 @@ def _portfolio_monitor(
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if entry_cfg is None:
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continue
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ranking_key = str(entry_cfg.get("ranking_key") or entry_cfg["percentile_key"])
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# The production row must replay the LIVE configuration: the runtime
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# qualification flag (Admin activation settings) instead of the frozen
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# research-variant gate, and the Admin exit policy instead of the
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# hardcoded 3x-trail/30d defaults. Research rows stay frozen so they
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# remain comparable across runs.
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use_live = bool(strategy.get("use_live_config"))
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exit_policy = str(strategy["exit_policy"])
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row_hold_days = hold_days
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trail_multiplier = ATR_TRAIL_MULTIPLIER
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live_exit_mode: str | None = None
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if use_live and live_exit_policy is not None:
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live_exit_mode = str(live_exit_policy.get("mode", "atr_trailing"))
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exit_policy = LIVE_EXIT_MODE_TO_SIM.get(live_exit_mode, "atr_trail3")
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row_hold_days = int(live_exit_policy.get("hold_days", hold_days))
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trail_multiplier = float(
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live_exit_policy.get("atr_multiplier", ATR_TRAIL_MULTIPLIER)
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)
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qualified_fn = (
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None if use_live
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else lambda c, config=entry_cfg: _qualifies_strategy_variant(c, config)
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)
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for lookback in PORTFOLIO_MONITOR_LOOKBACKS:
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start = _lookback_start(latest_ord, lookback["days"])
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sim = _simulate_portfolio(
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candidates,
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prices,
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_spy_closes,
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str(strategy["exit_policy"]),
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hold_days,
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qualified_fn=lambda c, config=entry_cfg: _qualifies_strategy_variant(c, config),
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exit_policy,
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row_hold_days,
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qualified_fn=qualified_fn,
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ranking_key=ranking_key,
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max_positions=int(entry_cfg["max_positions"]),
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risk_per_trade=float(entry_cfg["risk_per_trade"]),
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atr_trail_multiplier=trail_multiplier,
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start_date=start,
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include_curve=True,
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)
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@@ -1848,7 +1898,8 @@ def _portfolio_monitor(
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"description": strategy["description"],
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"is_production": bool(strategy.get("is_production")),
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"entry_variant": strategy["entry_variant"],
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"exit_policy": strategy["exit_policy"],
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"exit_policy": exit_policy,
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"live_exit_mode": live_exit_mode,
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"lookback": lookback["lookback"],
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"lookback_label": lookback["label"],
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**sim,
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@@ -2415,8 +2466,16 @@ async def run_backtest(
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exit_policy_rows = _exit_policy_sims(
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candidates, price_columns, spy_closes, hold_horizon
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)
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live_exit_policy: dict | None = None
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try:
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from app.services.paper_trade_service import get_exit_policy
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live_exit_policy = await get_exit_policy(db)
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except Exception:
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logger.exception("Live exit policy load failed; monitor uses defaults")
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portfolio_monitor_report = _portfolio_monitor(
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candidates, price_columns, spy_closes, hold_horizon
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candidates, price_columns, spy_closes, hold_horizon,
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live_exit_policy=live_exit_policy,
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)
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except Exception:
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logger.exception("Portfolio simulation failed")
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