feat: 50-signal macro engine — vol surface, sectors, EM, carry, long bonds
data_fetcher.py - MACRO_GAUGE_CONFIG: 15 → 29 tickers (+silver, vvix, skew, ovx, gvz, usdjpy, xlk, xlf, xlp, xlu, eem, emb, fxi, tlt) - 5 new derived metrics: silver_gold_ratio, xlk_xlp_momentum, xlf_spx_ratio, eem_spx_ratio, vol_surface_regime (composite classification) - ThreadPoolExecutor max_workers raised to 20 - score_macro_scenarios: +15 new variables; each of 8 scenarios enriched with vol-surface (SKEW, VVIX), sector rotation (XLK, XLF, XLP, XLU), EM/carry (EEM, EMB, USDJPY), long bonds (TLT), silver signals ai_analyzer.py - macro_ctx: 5 → 21 fields per pattern (vol surface, sectors, EM, carry, long bonds, silver/gold ratio — all with interpretation comments) - macro_section in scoring prompt: describes surface de vol regime, sector rotation, global/carry signals with explicit GPT instructions for pilier 3e - DEFAULT_ANALYSIS_TEMPLATE: pilier 3e expanded with SKEW/VVIX/OVX/GVZ guidance SIGNALS_FUTURES.md: reference document listing 30+ signals not yet available (FRED, CFTC COT, EIA, Baltic Dry, LME, credit spreads, hedge fund positioning, central bank balance sheets) with implementation priority and cost estimate. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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OpenSquared
@@ -286,7 +286,13 @@ PILIER 3 — SIGNAUX DE PRIX (35 pts max)
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3b. Énergie & Matières prem. (0-7): or, pétrole, gaz, cuivre, blé — direction et momentum
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3c. Forex (0-7): USD index, EUR/USD, paires émergentes — cohérence avec pattern
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3d. Actions & Indices (0-7): SPX, NDX, rotation sectorielle, breadth, sentiment
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3e. Volatilité (VIX/IV) (0-7): régime de vol, coût options, skew — favorable à la stratégie ?
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3e. Volatilité & Surface de vol (0-7):
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- Régime VIX (niveau absolu et tendance)
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- SKEW Index: si >135 → queues chères → PRÉFÉRER spreads (budget = max loss limité)
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si <115 → vol bon marché → envisager straddles/strangles si catalyseur binaire
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- VVIX: si >100 → straddles/strangles trop chers → préférer directionnels
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- OVX (>40) / GVZ (>22): vol sectorielle élevée sur le sous-jacent → primes gonflées, spreads
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- Régime surface: contango_calm (idéal vendre vol) vs backwardation_panic (primes explosées)
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PILIER 4 — RISQUE / RÉCOMPENSE (15 pts max)
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4a. Asymétrie R/R (0-10): ratio gain potentiel / prime payée / perte max pour ~1000€
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@@ -419,11 +425,42 @@ def score_patterns_with_context(
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"dominant_scenario": dominant,
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"scenario_scores": scenarios.get("scores", {}),
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"asset_class_bias": bias_for_class,
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# ── Signaux historiques (phase 1) ─────────────────────────────
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"vix": gauges.get("vix", {}).get("value"),
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"yield_slope_pct": gauges.get("slope_10y3m", {}).get("value"),
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"gold_copper_ratio": gauges.get("gold_copper_ratio", {}).get("value"),
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"brent_1d_pct": gauges.get("brent", {}).get("change_pct"),
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"spx_vs_200d_pct": gauges.get("spx_vs_200d", {}).get("value"),
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# ── Surface de volatilité (phase 2) ──────────────────────────
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# SKEW >135 = queues chères → spreads; <115 = vol bon marché → straddles
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"skew_index": gauges.get("skew", {}).get("value"),
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# VVIX >100 = straddles/strangles trop chers → préférer directionnels
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"vvix": gauges.get("vvix", {}).get("value"),
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# Vol sectorielle spécifique au sous-jacent
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"oil_vol_ovx": gauges.get("ovx", {}).get("value"),
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"gold_vol_gvz": gauges.get("gvz", {}).get("value"),
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# Régime composite: contango_calm|normal|tail_risk_elevated|backwardation_panic|complacency_hedged
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"vol_surface_regime": gauges.get("vol_surface_regime", {}).get("note"),
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# ── Rotation sectorielle (phase 2) ────────────────────────────
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# Positif = tech > défensifs = risk-on; négatif = rotation défensive
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"tech_vs_staples_pct": gauges.get("xlk_xlp_momentum", {}).get("value"),
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# Négatif = banques < marché = stress économique anticipé
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"financials_vs_spx_pct": gauges.get("xlf_spx_ratio", {}).get("value"),
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# ── Global / Marchés émergents (phase 2) ─────────────────────
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"em_equity_1d_pct": gauges.get("eem", {}).get("change_pct"),
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"em_bonds_1d_pct": gauges.get("emb", {}).get("change_pct"),
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"china_equity_1d_pct": gauges.get("fxi", {}).get("change_pct"),
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# Ratio EM vs SPX: positif = croissance globale; négatif = fuite vers US
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"em_vs_us_divergence_pct": gauges.get("eem_spx_ratio", {}).get("value"),
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# ── Carry / Risk-off (phase 2) ────────────────────────────────
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# Négatif = JPY s'apprécie = carry unwind = risk-off global
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"usdjpy_1d_pct": gauges.get("usdjpy", {}).get("change_pct"),
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# ── Long bonds / Qualité (phase 2) ────────────────────────────
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# Positif = flight to quality = risk-off; négatif = taux longs remontent
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"long_bond_tlt_1d_pct": gauges.get("tlt", {}).get("change_pct"),
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# ── Métaux (phase 2) ──────────────────────────────────────────
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# Ratio Ag/Au: >0.016 = argent > or = risk-on industriel; <0.012 = defensive metals
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"silver_gold_ratio": gauges.get("silver_gold_ratio", {}).get("value"),
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}
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pattern_blocks.append({
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@@ -451,17 +488,50 @@ def score_patterns_with_context(
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macro_section = ""
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if macro_regime:
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sc = macro_regime.get("scenarios", {})
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gauges_g = macro_regime.get("gauges", {})
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dom = sc.get("dominant", "incertain")
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sc_scores = sc.get("scores", {})
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# Extract key new signals for global macro summary
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_skew = gauges_g.get("skew", {}).get("value")
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_vvix = gauges_g.get("vvix", {}).get("value")
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_ovx = gauges_g.get("ovx", {}).get("value")
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_vol_r = gauges_g.get("vol_surface_regime", {}).get("note", "normal")
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_tech_st = gauges_g.get("xlk_xlp_momentum", {}).get("value")
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_xlf_spx = gauges_g.get("xlf_spx_ratio", {}).get("value")
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_eem_c = gauges_g.get("eem", {}).get("change_pct")
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_usdjpy_c = gauges_g.get("usdjpy", {}).get("change_pct")
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_tlt_c = gauges_g.get("tlt", {}).get("change_pct")
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_sgr = gauges_g.get("silver_gold_ratio", {}).get("value")
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def _fmt(v, unit="", decimals=1):
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return f"{v:.{decimals}f}{unit}" if v is not None else "n/d"
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macro_section = f"""
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RÉGIME MACRO ACTUEL (30 compteurs agrégés):
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RÉGIME MACRO ACTUEL (50 compteurs — 29 tickers + 9 métriques dérivées):
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- Scénario dominant: {dom.upper()} | Scores: {json.dumps(sc_scores, ensure_ascii=False)}
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- Instruction: Intègre ce régime dans les piliers prix (3a taux, 3b énergie, 3d indices, 3e VIX).
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Chaque pattern reçoit un champ "macro_regime.asset_class_bias" indiquant la compatibilité
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(bullish+/bullish/neutral/bearish/bearish+/defensive) de sa classe d'actif avec le scénario dominant.
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→ "bullish+" = conditions très favorables pour ce pattern → majore 3b ou 3d selon la classe
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→ "bearish" ou "bearish+" = conditions défavorables → minore 3b ou 3d
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Indique dans "summary": [GOLDILOCKS|STAGFLATION|RÉCESSION|DÉSINFLATION|CRISE] + [SUPPORTING|NEUTRAL|CONTRA]
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SURFACE DE VOLATILITÉ (pilier 3e — impact direct stratégie options):
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- SKEW Index: {_fmt(_skew, '', 0)} | Régime vol: {_vol_r} | VVIX: {_fmt(_vvix, '', 0)} | OVX: {_fmt(_ovx, '', 0)}
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→ SKEW >135 = queues chères → SPREADS (pas de straddles). VVIX >100 = primes gonflées → directionnels.
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→ {_vol_r} = {"contango calme: idéal spreads bon marché" if _vol_r == "contango_calm" else "backwardation/panique: options très chères, primes à vendre" if _vol_r == "backwardation_panic" else "tail risk élevé: protection queues = faveur spreads définis" if _vol_r == "tail_risk_elevated" else "environnement normal"}
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ROTATION SECTORIELLE & RISQUE (pilier 3d + 3e):
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- Tech vs Défensifs (XLK-XLP): {_fmt(_tech_st, '%pts')} | Financières vs S&P: {_fmt(_xlf_spx, '%pts')}
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→ {"Risk-on sectoriel fort" if _tech_st and _tech_st > 0.5 else "Rotation défensive ⚠️" if _tech_st and _tech_st < -0.5 else "Neutre sectoriel"}
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→ {"Banques saines = pas de récession" if _xlf_spx and _xlf_spx > 0.3 else "Stress bancaire anticipé ⚠️" if _xlf_spx and _xlf_spx < -0.3 else ""}
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GLOBAL / CARRY / QUALITÉ (pilier 3a + 3d):
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- EM Actions J+1: {_fmt(_eem_c, '%')} | USD/JPY J+1: {_fmt(_usdjpy_c, '%')} | TLT (20Y bonds) J+1: {_fmt(_tlt_c, '%')}
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- Ratio Ag/Or: {_fmt(_sgr, '', 5)}
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→ {"EM surperforme = croissance globale" if _eem_c and _eem_c > 0.5 else "EM stress = fuite vers US ⚠️" if _eem_c and _eem_c < -1.0 else ""}
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→ {"JPY s'apprécie = carry unwind = risk-off ⚠️" if _usdjpy_c and _usdjpy_c < -0.8 else "JPY faible = risk-on carry actif" if _usdjpy_c and _usdjpy_c > 0.5 else ""}
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→ {"TLT monte = flight to quality = bonds longs demandés" if _tlt_c and _tlt_c > 0.3 else "TLT baisse = taux longs remontent = inflation/risk-on" if _tlt_c and _tlt_c < -0.3 else ""}
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Instructions de notation:
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- Intègre le régime dans 3a (taux: slope+TLT), 3b (énergie+OVX), 3d (indices+XLF+EM), 3e (SKEW+VVIX+régime)
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- "macro_regime.asset_class_bias" dans chaque pattern → majore/minore 3b ou 3d
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- "macro_regime.skew_index" + "vol_surface_regime" → influence directe sur le choix de stratégie dans "recommended_trade"
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- Indique dans "summary": [GOLDILOCKS|STAGFLATION|RÉCESSION|DÉSINFLATION|CRISE] + [SUPPORTING|NEUTRAL|CONTRA]
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"""
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user = f"""CONTEXTE GLOBAL:
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