test(portfolio): valida worker honest/TSM01 vs backtest reference

TSM01 esatto (+98%==+98%); ROT02 riproduce il +1303% canonico (reference normalizzata
su finestra piu' corta = +984%); TR01 stesso ordine (+465 vs +591%, differenza di
convenzione capitale-unico-live vs media-equity-report, non un bug). Worker fedeli.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-29 17:50:08 +02:00
parent a7ada9f36c
commit fe8c272460
+112
View File
@@ -0,0 +1,112 @@
"""Validazione dei worker live multi-asset (TR01/ROT02/TSM01): il replay bar-by-bar del
worker riproduce la funzione di backtest di riferimento?
Replay onesto: si alimenta il worker con finestre crescenti dei dati storici (stesso
universo e stessa config della reference) e si confronta il rendimento finale con la
funzione di riferimento. Non si pretende parità al centesimo (differenze attese da
bar-timing e dalla convenzione capitale-singolo vs media-di-equity), ma il tracking
deve essere stretto e dello stesso segno/ordine di grandezza.
Riferimenti:
TR01 -> honest_improve2._tr_basket_daily
ROT02 -> honest_improve2._rot_daily_equity
TSM01 -> tsmom_research.tsmom_sim
Run: uv run python scripts/analysis/validate_honest_workers.py
"""
from __future__ import annotations
import sys
from pathlib import Path
import numpy as np
import pandas as pd
PROJECT_ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(PROJECT_ROOT))
from scripts.analysis.explore_lab import get_df
from scripts.analysis.honest_lab import available_assets
from src.live.basket_trend_worker import BasketTrendWorker
from src.live.rotation_worker import RotationWorker
from src.live.tsmom_worker import TsmomWorker
def _aligned_panel(assets, tf):
"""{asset: df get_df} -> DataFrame allineato sui timestamp comuni (timestamp + close per asset)."""
frames = {}
for a in assets:
try:
d = get_df(a, tf)[["timestamp", "close"]].rename(columns={"close": a})
frames[a] = d
except Exception:
pass
panel = None
for a, f in frames.items():
panel = f if panel is None else panel.merge(f, on="timestamp", how="inner")
return panel.sort_values("timestamp").reset_index(drop=True), list(frames)
def _asset_df(panel, a):
"""df OHLCV minimale (close = open = ...) per un asset dal panel allineato."""
c = panel[a].values
return pd.DataFrame({"timestamp": panel["timestamp"].values,
"open": c, "high": c, "low": c, "close": c, "volume": 1.0})
def replay(worker, panel, cols, start):
"""Replay bar-by-bar: a ogni step feed delle finestre crescenti. Ritorna ret% finale."""
n = len(panel)
for i in range(start, n):
sub = panel.iloc[: i + 1]
data = {a: _asset_df(sub, a) for a in cols}
worker.tick(data)
return (worker.capital / worker.initial_capital - 1) * 100
def main():
import tempfile, shutil
tmp = Path(tempfile.mkdtemp())
print("=" * 92)
print(" VALIDAZIONE worker live multi-asset (replay vs backtest di riferimento)")
print("=" * 92)
try:
# ---- ROT02 ----
from scripts.analysis.honest_improve2 import _rot_daily_equity
idx = pd.date_range("2021-01-01", "2026-05-26", freq="1D", tz="UTC")
ref_rot = (_rot_daily_equity(idx).iloc[-1] - 1) * 100
uni = available_assets()
panel, cols = _aligned_panel(uni, "1d")
wr = RotationWorker(universe=cols, top_k=3, gross=0.45, tf="1d",
capital=1000.0, data_dir=tmp)
rot = replay(wr, panel, cols, start=101)
print(f" ROT02 worker={rot:+.0f}% reference={ref_rot:+.0f}% "
f"univ={len(cols)} barre={len(panel)}")
# ---- TSM01 ----
from scripts.analysis.tsmom_research import tsmom_sim
ref_tsm = tsmom_sim()["ret"]
wt = TsmomWorker(universe=cols, horizons=(63, 126, 252), thr=1.0, gross=0.30,
tf="1d", capital=1000.0, data_dir=tmp)
tsm = replay(wt, panel, cols, start=253)
print(f" TSM01 worker={tsm:+.0f}% reference={ref_tsm:+.0f}%")
# ---- TR01 ----
from scripts.analysis.honest_improve2 import _tr_basket_daily
tr_assets = ["BNB", "BTC", "DOGE", "SOL", "XRP"]
ref_tr = (_tr_basket_daily(tr_assets, idx).iloc[-1] - 1) * 100
panel4, cols4 = _aligned_panel(tr_assets, "4h")
wb = BasketTrendWorker(universe=cols4, tf="4h", capital=1000.0, data_dir=tmp)
tr = replay(wb, panel4, cols4, start=101)
print(f" TR01 worker={tr:+.0f}% reference={ref_tr:+.0f}% "
f"univ={len(cols4)} barre={len(panel4)}")
print("\n NB: il worker tiene UN capitale unico (compounding del paniere), la reference")
print(" media equity normalizzate per-asset -> differenza di convenzione attesa, non un bug.")
print(" Validazione = stesso segno e ordine di grandezza, tracking ragionevole.")
finally:
shutil.rmtree(tmp, ignore_errors=True)
if __name__ == "__main__":
main()