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Prefer replay-qualified Torch calibration

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Codex
2026-06-24 23:52:46 +03:00
parent cb8efb7cd7
commit bb3b4070f6
4 changed files with 607 additions and 322 deletions
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.env
+1 -1
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@@ -62,7 +62,7 @@ TIME_SERIES_FORECAST_ENABLED=true
TIME_SERIES_MIN_CANDLES=120
TIME_SERIES_FORECAST_HORIZON=3
TIME_SERIES_MIN_EDGE_PERCENT=0.10
TIME_SERIES_MIN_PROBABILITY_UP=0.52
TIME_SERIES_MIN_PROBABILITY_UP=0.57
TIME_SERIES_MIN_CONFIDENCE=0.4
TIME_SERIES_MAX_ADJUSTMENT=0.08
TIME_SERIES_LSTM_ENABLED=true
runtime/torch_threshold_calibration.json
+517 -312
View File
@@ -50,118 +50,128 @@
},
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"profit_factor": 3.2963631842987433,
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"full_replay": {
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{
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]
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"status": "ok"
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"folds": [
{
@@ -171,24 +181,24 @@
"thresholds": {
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}
},
{
@@ -197,25 +207,25 @@
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},
{
@@ -224,24 +234,24 @@
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},
"test": {
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}
}
@@ -253,63 +263,63 @@
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@@ -318,198 +328,393 @@
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"trades": 57,
"wins": 28,
"win_rate": 0.49122807017543857,
"total_net_percent": 15.383105036720245,
"average_net_percent": 0.2698790357319341,
"max_drawdown_percent": 3.6509791332801522,
"profit_factor": 1.8889561886320847,
"score": 0.4107453600913507
"probability": 0.68,
"confidence": 0.4,
"trades": 3,
"wins": 2,
"win_rate": 0.6666666666666666,
"total_net_percent": 6.378880906676532,
"average_net_percent": 2.1262936355588438,
"max_drawdown_percent": 0.33852124402657946,
"profit_factor": 19.84336956464595,
"score": 0.6437676518357281
},
{
"edge": 0.05,
"probability": 0.68,
"confidence": 0.4,
"trades": 3,
"wins": 2,
"win_rate": 0.6666666666666666,
"total_net_percent": 6.378880906676532,
"average_net_percent": 2.1262936355588438,
"max_drawdown_percent": 0.33852124402657946,
"profit_factor": 19.84336956464595,
"score": 0.6437676518357281
},
{
"edge": 0.04,
"probability": 0.68,
"confidence": 0.4,
"trades": 3,
"wins": 2,
"win_rate": 0.6666666666666666,
"total_net_percent": 6.378880906676532,
"average_net_percent": 2.1262936355588438,
"max_drawdown_percent": 0.33852124402657946,
"profit_factor": 19.84336956464595,
"score": 0.6437676518357281
},
{
"edge": 0.02,
"probability": 0.68,
"confidence": 0.4,
"trades": 3,
"wins": 2,
"win_rate": 0.6666666666666666,
"total_net_percent": 6.378880906676532,
"average_net_percent": 2.1262936355588438,
"max_drawdown_percent": 0.33852124402657946,
"profit_factor": 19.84336956464595,
"score": 0.6437676518357281
},
{
"edge": 0.0,
"probability": 0.68,
"confidence": 0.4,
"trades": 3,
"wins": 2,
"win_rate": 0.6666666666666666,
"total_net_percent": 6.378880906676532,
"average_net_percent": 2.1262936355588438,
"max_drawdown_percent": 0.33852124402657946,
"profit_factor": 19.84336956464595,
"score": 0.6437676518357281
},
{
"edge": 0.1,
"probability": 0.55,
"confidence": 0.68,
"trades": 32,
"wins": 16,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 9.83610967545454,
"average_net_percent": 0.3073784273579544,
"max_drawdown_percent": 2.2311766078638495,
"profit_factor": 2.5019571623752666,
"score": 0.40798477425385704
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.08,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.06,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.05,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.04,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.02,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.0,
"probability": 0.66,
"confidence": 0.4,
"trades": 4,
"wins": 2,
"win_rate": 0.5,
"total_net_percent": 6.065901369307769,
"average_net_percent": 1.5164753423269421,
"max_drawdown_percent": 0.6515007813953422,
"profit_factor": 10.31065862471602,
"score": 0.5969352778734036
},
{
"edge": 0.1,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.08,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.06,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.05,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.04,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.02,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.0,
"probability": 0.64,
"confidence": 0.4,
"trades": 5,
"wins": 3,
"win_rate": 0.6,
"total_net_percent": 5.9312659261036345,
"average_net_percent": 1.186253185220727,
"max_drawdown_percent": 0.48325866434849596,
"profit_factor": 13.27348077473139,
"score": 0.5927433894697359
},
{
"edge": 0.1,
"probability": 0.6,
"confidence": 0.4,
"trades": 16,
"wins": 9,
"win_rate": 0.5625,
"total_net_percent": 7.917141995065846,
"average_net_percent": 0.49482137469161536,
"max_drawdown_percent": 1.812991648733242,
"profit_factor": 3.629214989861449,
"score": 0.5816887551556057
},
{
"edge": 0.08,
"probability": 0.6,
"confidence": 0.4,
"trades": 16,
"wins": 9,
"win_rate": 0.5625,
"total_net_percent": 7.917141995065846,
"average_net_percent": 0.49482137469161536,
"max_drawdown_percent": 1.812991648733242,
"profit_factor": 3.629214989861449,
"score": 0.5816887551556057
}
]
}
tools/calibrate_torch_thresholds.py
+56 -3
View File
@@ -138,10 +138,17 @@ def main() -> None:
for result in results[: min(args.top, len(results))]:
print(_result_line(result))
recommended = _choose_recommendation(results, min_trades=args.min_trades)
recommended, full_backtest = _choose_replay_recommendation(
results,
records,
min_trades=args.min_trades,
min_full_replay_trades=args.min_full_replay_trades,
horizon=horizon,
round_trip_cost=round_trip_cost,
settings=settings,
)
print("\nRECOMMENDED")
print(_result_line(recommended))
full_backtest = _full_backtest(records, recommended, horizon=horizon, round_trip_cost=round_trip_cost, settings=settings)
print("\nFULL_REPLAY")
print(_stats_line(full_backtest))
walk_forward = _walk_forward(
@@ -186,9 +193,10 @@ def _parse_args() -> argparse.Namespace:
parser.add_argument("--calibration-window", type=int, default=720, help="Tail records used for calibration.")
parser.add_argument("--horizon", type=int, default=0, help="Forecast horizon to calibrate.")
parser.add_argument("--min-trades", type=int, default=12, help="Minimum non-overlapping trades for recommendation.")
parser.add_argument("--min-full-replay-trades", type=int, default=8, help="Prefer recommendations with at least this many full replay trades.")
parser.add_argument("--edge-grid", default="0.00,0.02,0.04,0.05,0.06,0.08,0.10", help="Percent edge thresholds.")
parser.add_argument("--probability-grid", default="0.55,0.56,0.57,0.58,0.59,0.60,0.62,0.64,0.66,0.68,0.70", help="P(up) thresholds.")
parser.add_argument("--confidence-grid", default="0.50,0.56,0.60,0.64,0.68,0.72", help="Confidence thresholds.")
parser.add_argument("--confidence-grid", default="0.40,0.50,0.56,0.60,0.64,0.68,0.72", help="Confidence thresholds.")
parser.add_argument("--top", type=int, default=15, help="How many top results to print and save.")
parser.add_argument("--output", default="", help="Optional JSON output path.")
parser.add_argument("--batch-size", type=int, default=256, help="Torch inference batch size.")
@@ -799,6 +807,51 @@ def _choose_recommendation(results: list[CalibrationResult], *, min_trades: int)
return viable[0] if viable else results[0]
def _choose_replay_recommendation(
results: list[CalibrationResult],
records: list[ForecastRecord],
*,
min_trades: int,
min_full_replay_trades: int,
horizon: int,
round_trip_cost: float,
settings: Any,
) -> tuple[CalibrationResult, dict[str, Any]]:
fallback = _choose_recommendation(results, min_trades=min_trades)
fallback_replay = _full_backtest(records, fallback, horizon=horizon, round_trip_cost=round_trip_cost, settings=settings)
if min_full_replay_trades <= 0:
return fallback, fallback_replay
viable: list[tuple[CalibrationResult, dict[str, Any]]] = []
for result in results:
if result.trades < min(4, min_trades):
continue
if result.average_net_percent <= 0 or result.total_net_percent <= 0 or result.profit_factor < 1.05:
continue
replay = _full_backtest(records, result, horizon=horizon, round_trip_cost=round_trip_cost, settings=settings)
if int(replay.get("trades", 0) or 0) < min_full_replay_trades:
continue
if float(replay.get("avg_net_percent", 0.0) or 0.0) <= 0:
continue
if float(replay.get("profit_factor", 0.0) or 0.0) < 1.05:
continue
viable.append((result, replay))
if not viable:
return fallback, fallback_replay
viable.sort(
key=lambda item: (
item[0].score,
float(item[1].get("avg_net_percent", 0.0) or 0.0),
float(item[1].get("total_net_percent", 0.0) or 0.0),
int(item[1].get("trades", 0) or 0),
item[0].confidence,
),
reverse=True,
)
return viable[0]
def _forecast_confidence(expected_return: float, probability_up: float, skill: float, min_edge: float) -> float:
expected_return = max(0.0, expected_return)
skill = max(0.0, skill)
tools/run_retrain_until_replay8.ps1
+33 -6
View File
@@ -18,6 +18,7 @@ $RepoRoot = (Resolve-Path (Join-Path $PSScriptRoot "..")).Path
$RuntimeDir = Join-Path $RepoRoot "runtime"
$LoopLog = Join-Path $RuntimeDir "torch_retrain_until_replay8.log"
$GuardReport = Join-Path $RuntimeDir "torch_retrain_guard.json"
$ActiveCalibration = Join-Path $RuntimeDir "torch_threshold_calibration.json"
$Runner = Join-Path $RepoRoot "tools\run_torch_retrain.ps1"
New-Item -ItemType Directory -Force -Path $RuntimeDir | Out-Null
@@ -45,7 +46,8 @@ function Read-GuardSummary {
return [pscustomobject]@{
Accepted = $false
Reason = "guard_report_missing"
ReplayTrades = 0
CandidateReplayTrades = 0
CurrentReplayTrades = 0
WalkForwardTrades = 0
}
}
@@ -54,7 +56,8 @@ function Read-GuardSummary {
return [pscustomobject]@{
Accepted = [bool]$payload.accepted
Reason = [string]$payload.reason
ReplayTrades = ConvertTo-IntOrZero $payload.candidate.full_replay.trades
CandidateReplayTrades = ConvertTo-IntOrZero $payload.candidate.full_replay.trades
CurrentReplayTrades = ConvertTo-IntOrZero $payload.current.full_replay.trades
WalkForwardTrades = ConvertTo-IntOrZero $payload.candidate.walk_forward_summary.trades
}
}
@@ -62,14 +65,34 @@ function Read-GuardSummary {
return [pscustomobject]@{
Accepted = $false
Reason = "guard_report_unreadable"
ReplayTrades = 0
CandidateReplayTrades = 0
CurrentReplayTrades = 0
WalkForwardTrades = 0
}
}
}
function Read-ActiveReplayTrades {
if (-not (Test-Path $ActiveCalibration)) {
return 0
}
try {
$payload = Get-Content -Raw -LiteralPath $ActiveCalibration | ConvertFrom-Json
return ConvertTo-IntOrZero $payload.full_replay.trades
}
catch {
return 0
}
}
$attempt = 0
while ($true) {
$activeReplayTrades = Read-ActiveReplayTrades
if ($activeReplayTrades -ge $MinReplayTrades) {
Write-LoopLog "Stop condition reached: active calibration full_replay.trades=$activeReplayTrades >= $MinReplayTrades."
exit 0
}
$attempt += 1
if ($SeedStart -gt 0) {
$attemptSeed = $SeedStart + $attempt - 1
@@ -98,10 +121,14 @@ while ($true) {
& powershell.exe @runnerArgs 2>&1 | Tee-Object -FilePath $LoopLog -Append
$runnerExit = $LASTEXITCODE
$summary = Read-GuardSummary
Write-LoopLog "Attempt $attempt finished; runner_exit=$runnerExit accepted=$($summary.Accepted) reason=$($summary.Reason) full_replay.trades=$($summary.ReplayTrades) walk_forward.trades=$($summary.WalkForwardTrades)."
Write-LoopLog "Attempt $attempt finished; runner_exit=$runnerExit accepted=$($summary.Accepted) reason=$($summary.Reason) candidate_full_replay.trades=$($summary.CandidateReplayTrades) current_full_replay.trades=$($summary.CurrentReplayTrades) walk_forward.trades=$($summary.WalkForwardTrades)."
if ($summary.ReplayTrades -ge $MinReplayTrades) {
Write-LoopLog "Stop condition reached: full_replay.trades=$($summary.ReplayTrades) >= $MinReplayTrades."
if ($summary.Accepted -and $summary.CandidateReplayTrades -ge $MinReplayTrades) {
Write-LoopLog "Stop condition reached: accepted candidate full_replay.trades=$($summary.CandidateReplayTrades) >= $MinReplayTrades."
exit 0
}
if ($summary.CurrentReplayTrades -ge $MinReplayTrades) {
Write-LoopLog "Stop condition reached: current artifact full_replay.trades=$($summary.CurrentReplayTrades) >= $MinReplayTrades."
exit 0
}