Adriano Dal Pastro
de72e3ce1f
Second agent wave (skyhook-improve-v2, 14 DD-reduction families, each adversarially verified by 2 skeptics) beats the prior winner on the only unmet goal (DD<30%). Winner = ASYM_LS -> promoted to engine as SKH01_V2_DD: same signal (ptn_n=45, vola[35,95], vol_lo=0, exit-bars 24/16) but exits switched from ATR to FIXED-PCT ASYMMETRIC — long sl4%/tp10%, short sl2%(tighter)/tp8%. The tight short %-SL caps the per-trade loss that forms the maxDD in vol spikes. Verified (sk.study, independent re-run): standalone maxDD BTC 21.4% / ETH 27.4% (<30%), minFull +0.99, minHold +1.26, causality 0/400 both assets, fee-surviving to 0.40%RT, marginal vs TP01 ADDS (corr 0.09, in-sample edge, robust_oos, multicut, clean-year +0.57), blend 0.75*TP01+0.25*SKH uplift_hold +0.87; blend 50/50 full 1.84/hold 1.59/DD 10.7%. Plateau (not knife-edge); both skeptics holds_up=high, killer=null. Engine: per-direction short exit overrides (exit_mode_short/sl_*_short/tp_*_short), backward-compatible (None -> symmetric, V1/intermediate-winner unchanged). +3 tests (8/8 pass). Lessons: DD is cut by changing the exit MECHANISM (%-SL, L/S asymmetry, ensembles), NOT by entry-only kill-switch / vol-target / cadence. PATTERN_CONF killed as overfit (knife-edge). PCTL_DD unverified (rate-limit) and ENS_PARAM/TPSL_DD recency/hedge-loaded -> forward-monitor. NOT yet wired to live sleeves: re-verify blend@0.25 + causality on execution code before deploy. Includes both waves' research scripts (runs/SKH_* wave 1, runs/SKH2_* wave 2). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
19 lines
879 B
Python
19 lines
879 B
Python
import sys
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sys.path.insert(0, "/opt/docker/PythagorasGoal/scripts/research/skyhook")
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import skyhooklib as sk
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from src.strategies.skyhook import SkyhookParams
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V1 = SkyhookParams(ptn_n=55, sl_atr=2.5, tp_atr=6.0, vola_lo=35.0, vola_hi=95.0, vol_lo=0.0)
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print("=== V1 reference ===")
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rep = sk.study("SKH01-V1", V1)
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print(sk.fmt(rep))
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print("causality:", sk.causality(V1))
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mg = sk.marginal(V1)
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keys = ("corr_full","corr_hold","marginal_verdict","has_insample_edge","is_hedge",
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"robust_oos","multicut_persistent","clean_year_uplift","jackknife_min_uplift",
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"cand_insample_sharpe","cand_full_sharpe")
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print("marginal:", {k: mg.get(k) for k in keys})
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print("blend w25 uplift_hold:", mg.get("blends",{}).get("w25",{}).get("uplift_hold"))
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print("blend w25 uplift_full:", mg.get("blends",{}).get("w25",{}).get("uplift_full"))
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print("multicut:", mg.get("multicut_uplift"))
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