feat(research): FR01 Hurst-Calm Fade + analisi per-anno/mercato (ricerca 100 agenti)

Esito ricerca frattali x regime ARGO (171 agenti): - FR01_hurst_calm_fade.py: vincitore = fade gateato da hurst<0.55 (anti-persistente) + dvol_pct<0.4 (DVOL bassa). OOS Sharpe 3.73 BTC, 6/6 anni positivi su BTC+ETH, corr bassa coi fade esistenti (MR01 +0.17/MR02 +0.08/MR07 -0.03) -> diversificatore non ridondante. - fractal_argo_peryear.py: analisi per-anno/regime-mercato dei top candidati. - diario 2026-06-02: verdetto completo. Finding chiave: prior ARGO 'VRP>0=range=fade' SMENTITO, l'edge robusto e' su VRP<0 + DVOL bassa. Diversificatori, NON spodestano PORT06 (OOS Sharpe 8.19). Branch di ricerca. Deploy bloccato da: verifica corr sul MASTER intero + wiring DVOL live nel runner. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-02 07:22:10 +00:00
parent 5f229cd66e
commit 7005763517
3 changed files with 284 additions and 0 deletions
@@ -0,0 +1,86 @@
+import sys; sys.path.insert(0,".")
+import numpy as np, pandas as pd
+from scripts.analysis.regime_lab import load_features
+from scripts.analysis.explore_lab import atr
+
+FEE=0.001; LEV=3
+
+def build(df, gate, k=2.5, sl_atr=2.0, mb=24, bb=50):
+    c=df['close'].values; a=atr(df,14)
+    ma=pd.Series(c).rolling(bb).mean().values; sd=pd.Series(c).rolling(bb).std().values
+    ent=[]
+    for i in range(bb+14,len(c)-1):
+        if np.isnan(sd[i]) or sd[i]==0 or np.isnan(a[i]): continue
+        if not gate(df,i): continue
+        if c[i]<ma[i]-k*sd[i]: d,sl=1,c[i]-sl_atr*a[i]
+        elif c[i]>ma[i]+k*sd[i]: d,sl=-1,c[i]+sl_atr*a[i]
+        else: continue
+        ent.append({'i':i,'d':d,'tp':ma[i],'sl':sl,'mb':mb})
+    return ent
+
+def per_year(df, ent):
+    """replay intrabar fedele (sl-first, tp, poi max_bars@close) -> per anno {n,ret%,win%}."""
+    h=df['high'].values; l=df['low'].values; c=df['close'].values
+    ts=pd.to_datetime(df['timestamp'],unit='ms',utc=True)
+    Y={}
+    last=-1
+    for e in ent:
+        i=e['i']
+        if i<=last: continue
+        d=e['d']; tp=e['tp']; sl=e['sl']; j=min(i+e['mb'],len(c)-1)
+        exit_p=c[j]
+        for t in range(i+1,j+1):
+            if d==1:
+                if l[t]<=sl: exit_p=sl; j=t; break
+                if h[t]>=tp: exit_p=tp; j=t; break
+            else:
+                if h[t]>=sl: exit_p=sl; j=t; break
+                if l[t]<=tp: exit_p=tp; j=t; break
+        ret=(exit_p-c[i])/c[i]*d*LEV - FEE*LEV
+        last=j; yr=ts.iloc[i].year
+        if yr not in Y: Y[yr]=[0,0.0,0]
+        Y[yr][0]+=1; Y[yr][1]+=ret*100; Y[yr][2]+= (ret>0)
+    return Y
+
+# gate functions
+def g_hurst_calm(df,i): return df['hurst'].iloc[i]<0.55 and not np.isnan(df['dvol_pct'].iloc[i]) and df['dvol_pct'].iloc[i]<0.40
+def g_vrp_neg(df,i):    return not np.isnan(df['vrp'].iloc[i]) and df['vrp'].iloc[i]<0
+def g_hig_vrp(df,i):
+    hi=df['higuchi'].iloc[i]; return (not np.isnan(hi)) and hi>1.5 and (not np.isnan(df['vrp'].iloc[i])) and df['vrp'].iloc[i]<0
+def g_none(df,i): return True
+
+STRATS=[("HurstCalmFade (hurst<.55 & DVOL<p40)",g_hurst_calm),
+        ("VRP<0 Fade (core driver)",g_vrp_neg),
+        ("HigVRP Fade (Higuchi>1.5 & VRP<0)",g_hig_vrp),
+        ("Fade NUDA (no gate, baseline)",g_none)]
+
+# regime mercato BTC per anno (da BTC close annuale)
+btc=load_features("BTC","1d")
+bts=pd.to_datetime(btc['timestamp'],unit='ms',utc=True); bc=btc['close'].values
+mkt={}
+for yr in range(2021,2027):
+    m=(bts.dt.year==yr).values
+    if m.sum()>5:
+        r=(bc[m][-1]/bc[m][0]-1)*100
+        mkt[yr]=("BULL" if r>40 else "BEAR" if r<-30 else "RANGE", r)
+
+for asset in ("BTC","ETH"):
+    df=load_features(asset,"1h")
+    print(f"\n{'='*78}\n  {asset} 1h — performance per anno (somma ret% per-trade, netto leva3x+fee0.10%)\n{'='*78}")
+    print(f"  {'Strategia':<40} " + " ".join(f"{y}" for y in range(2021,2027)))
+    for name,g in STRATS:
+        ent=build(df,g); Y=per_year(df,ent)
+        cells=[]
+        for y in range(2021,2027):
+            if y in Y and Y[y][0]>0:
+                cells.append(f"{Y[y][1]:+5.0f}")
+            else: cells.append("   . ")
+        print(f"  {name:<40} " + " ".join(cells))
+    # riga trades/anno per la strategia principale
+    ent=build(df,g_hurst_calm); Y=per_year(df,ent)
+    tr=" ".join(f"{Y.get(y,[0])[0]:>5}" for y in range(2021,2027))
+    print(f"  {'(HurstCalmFade trades/anno)':<40} {tr}")
+
+print(f"\n  REGIME MERCATO BTC per anno (ret% annuale prezzo):")
+for y in range(2021,2027):
+    if y in mkt: print(f"    {y}: {mkt[y][0]:6} ({mkt[y][1]:+.0f}%)")