Config · stock

atlas dual_momentum dynamo levetf megahold retirement401k sector_etf sector_pulse stock_scorer trendrunner

execution.json STOCK_SCORER

/Users/mvr113/QuantOS/engines/stock_scorer/algo_core/config/execution.json

{
    "_note": "Stock Scorer master config \u2014 single source of truth for all strategy parameters. core.py reads this at startup; no values are hardcoded in Python. Edit here; next run picks it up automatically. CREDENTIALS (gmail_password, anthropic_api_key) must come from env vars \u2014 never stored here.",
    "execution_mode": "FULL_AUTO",
    "order_type": "market",
    "output": {
        "_note": "Email config. Credentials (gmail_password) must be in EMAIL_FROM_PWD env var.",
        "email_recipients": [
            "mvrjer99@gmail.com",
            "julia.reddy@gmail.com"
        ],
        "sender_email": "ighir999@gmail.com",
        "email_top_n": 5
    },
    "universe": {
        "_note": "Max tickers evaluated per run. Universe = S&P 500 + Nasdaq 100 union (507 tickers as of 2026-07-20) + any held orphan positions.",
        "max_tickers": 1000
    },
    "portfolio": {
        "_note": "max_weight and min_weight are fractions (0.10 = 10%). max_sector_pct and max_industry_pct are fractions. max_positions/hold_rank_limit below are ONLY the CONFIG fallback used if the regime check itself throws (pipeline.py get_regime()'s exception path) -- for real, day-to-day position sizing see the 'regime_positions' section instead, which core.py now actually reads (moved out of pipeline.py's hardcoded table 2026-07-20).",
        "max_positions": 15,
        "hold_rank_limit": 15,
        "max_weight": 0.1,
        "min_weight": 0.02,
        "max_sector_pct": 0.4,
        "max_industry_pct": 0.3,
        "min_composite_score": {
            "_note": "Per-regime composite_score gate (0-100). Dict = regime-keyed + 'default' fallback. Flat number = always applies. 0 = disabled.",
            "default": 0,
            "BUY": 0,
            "NO-BUY": 0,
            "RISK-OFF": 50,
            "CRISIS": 70
        }
    },
    "regime_positions": {
        "_note": "The REAL, live regime-adaptive position table (n_pos = max positions to hold, hold_rank_limit = sell-below-this-rank hysteresis). Moved out of pipeline.py's hardcoded get_regime() 2026-07-20 -- core.py now reads this section directly as CONFIG['regime_positions'], making this file the actual single source of truth for it (previously this table was hardcoded in Python despite this file's top-level claim that nothing is). Widened 1.5x from the pre-2026-07-20 table (CRISIS 2/3, RISK-OFF severe 4/6, RISK-OFF normal 8/10, NO-BUY 12/15, BUY+alpha 12/18, BUY+normal 18/20) after research/backtest_stock_scorer.py --sweep (point-in-time S&P 500 membership from Wikipedia's changes log, real volume-based sqrt market-impact costs, margin loan interest modeled at 8%/yr) swept a uniform scale factor over this table and found 1.5x Pareto-dominant over the prior 1.0x table in BOTH the margin and retirement account scenarios simultaneously -- higher CAGR, higher Sharpe, AND smaller max drawdown, not just a risk/return trade-off. Margin: CAGR 139.5%->152.6%, Sharpe 3.35->4.07, MaxDD -40.2%->-35.1%. Retirement: CAGR 59.9%->64.2%, Sharpe 2.42->2.87, MaxDD -21.2%->-18.5%. Scales beyond 1.5x (2x, 3x) kept raising Sharpe but CAGR fell -- the ~500-ticker S&P 500 + Nasdaq 100 universe runs out of genuinely differentiated momentum leaders to dilute into past that point. Caveat: this backtest window (2022-2026) is one continuous bull market with few real regime transitions, so treat this as directional evidence for more breadth, not a guarantee it holds in a bear/choppy regime -- worth re-checking after this config has lived through one. max_weight/min_weight per regime (still in pipeline.py, not moved here) were left unchanged: the backtest modeled equal-weighted returns across held names, not these caps, so they weren't part of what was actually validated. Edit n_pos/hold_rank_limit here and it takes effect on the next run -- no code change needed.",
        "CRISIS": {
            "n_pos": 0,
            "hold_rank_limit": 5
        },
        "RISK_OFF_SEVERE": {
            "n_pos": 2,
            "hold_rank_limit": 9
        },
        "RISK_OFF_NORMAL": {
            "n_pos": 5,
            "hold_rank_limit": 15
        },
        "NO_BUY": {
            "n_pos": 10,
            "hold_rank_limit": 23
        },
        "BUY_ALPHA": {
            "n_pos": 15,
            "hold_rank_limit": 27
        },
        "BUY_NORMAL": {
            "n_pos": 15,
            "hold_rank_limit": 30
        }
    },
    "risk": {
        "_note": "stop_loss_pct: whole % (e.g. -7.0 = -7%). intraday_stop_pct: same-day drop % triggering sell. portfolio_drawdown_halt_pct: avg port P&L % below which new BUYs suppressed. hard_trailing_stop_pct: fraction (0.06 = 6%). atr_stop_tiers: [[ema_extension, atr_mult], ...]. trim_tiers: [[ema_extension, action], ...]. take_profit_pct: whole % gain to exit (25 = sell at +25%).",
        "max_de_general": 8.0,
        "max_de_financial": 30.0,
        "stop_loss_pct": -4.0,
        "intraday_stop_pct": -6.0,
        "portfolio_drawdown_halt_pct": -4.0,
        "hard_trailing_stop_pct": 0.06,
        "take_profit_pct": 20,
        "atr_stop_multiplier": 1.5,
        "atr_rsi_tighten": 78.0,
        "euphoria_rsi_trim": 85.0,
        "euphoria_ema_trim": 0.15,
        "min_rsi_screen": 45.0,
        "require_price_above_ema50": true,
        "require_price_above_ema200": true,
        "atr_stop_tiers": [
            [
                0.08,
                1.5
            ],
            [
                0.15,
                1.0
            ]
        ],
        "trim_tiers": [
            [
                0.12,
                "TRIM"
            ],
            [
                0.18,
                "TRIM 25%"
            ],
            [
                0.25,
                "TRIM 25% MORE"
            ]
        ],
        "earnings_guard_days": 2
    },
    "extended_hours": {
        "_note": "Pre/post-market order filters. Volumes are share counts, not dollar amounts.",
        "pre_market_min_volume": 5000,
        "pre_market_min_pct_change": 0.5,
        "post_market_min_volume": 2000,
        "post_market_min_pct_change": 0.3
    },
    "regime": {
        "_note": "vix_threshold: VIX level above which pipeline.py classifies 'stress'/RISK-OFF (was hardcoded to 25 in core.py with no config entry until 2026-07-03 \u2014 real trading impact, now visible/overridable here). vix_crisis_threshold: absolute VIX level for CRISIS. vix_crisis_spike_pct: intraday spike % that also triggers CRISIS. vix_spike_halt_pct: % single-day VIX spike that suppresses new BUYs.",
        "vix_threshold": 25,
        "vix_spike_halt_pct": 10.0,
        "vix_crisis_threshold": 40,
        "vix_crisis_spike_pct": 15.0
    },
    "volatility_alerts": {
        "_note": "Display-only alert banners in the report. Do not affect trade decisions.",
        "spy_move_threshold": 1.5,
        "vix_level_threshold": 25.0,
        "vix_spike_threshold": 20.0,
        "volume_surge_threshold": 1.5
    },
    "weights_buy": {
        "_note": "Factor weights for BUY regime. Must sum to 1.0.",
        "momentum": 0.35,
        "volume_mom": 0.1,
        "quality": 0.2,
        "growth": 0.2,
        "value": 0.08,
        "risk": 0.07
    },
    "weights_riskoff": {
        "momentum": 0.15,
        "volume_mom": 0.05,
        "quality": 0.3,
        "growth": 0.2,
        "value": 0.12,
        "risk": 0.18
    },
    "weights_nobuy": {
        "momentum": 0.2,
        "volume_mom": 0.07,
        "quality": 0.28,
        "growth": 0.18,
        "value": 0.12,
        "risk": 0.15
    },
    "weights_crisis": {
        "momentum": 0.05,
        "volume_mom": 0.02,
        "quality": 0.4,
        "growth": 0.2,
        "value": 0.15,
        "risk": 0.18
    },
    "alpha_pts": {
        "_note": "Point bonuses added to composite score for each signal type.",
        "earn_beat": 6.0,
        "insider": 8.0,
        "institutional": 5.0,
        "analyst_rev": 4.0,
        "short_contra": 2.0,
        "proximity_52wh": 5.0
    },
    "scoring": {
        "_note": "Additional scoring bonuses.",
        "pt_upside_max_pts": 5.0,
        "accel_max_pts": 4.0,
        "volume_thrust_pts": 6.0
    },
    "sector_regime_weights": {
        "_note": "Multiplier applied to composite score after factor weighting.",
        "BUY": {
            "Technology": 1.15,
            "Communication Services": 1.1,
            "Consumer Discretionary": 1.08,
            "Industrials": 1.05,
            "Health Care": 1.0,
            "Financials": 1.0,
            "Energy": 0.95,
            "Materials": 0.95,
            "Real Estate": 0.9,
            "Consumer Staples": 0.88,
            "Utilities": 0.85
        },
        "RISK-OFF": {
            "Technology": 0.85,
            "Communication Services": 0.88,
            "Consumer Discretionary": 0.82,
            "Industrials": 0.9,
            "Health Care": 1.15,
            "Financials": 0.92,
            "Energy": 1.08,
            "Materials": 1.0,
            "Real Estate": 1.02,
            "Consumer Staples": 1.18,
            "Utilities": 1.2
        },
        "NO-BUY": {
            "Technology": 0.9,
            "Communication Services": 0.92,
            "Consumer Discretionary": 0.88,
            "Industrials": 0.94,
            "Health Care": 1.1,
            "Financials": 0.96,
            "Energy": 1.05,
            "Materials": 1.0,
            "Real Estate": 1.03,
            "Consumer Staples": 1.12,
            "Utilities": 1.15
        },
        "CRISIS": {
            "Technology": 0.6,
            "Communication Services": 0.65,
            "Consumer Discretionary": 0.55,
            "Industrials": 0.7,
            "Health Care": 1.3,
            "Financials": 0.65,
            "Energy": 1.05,
            "Materials": 0.75,
            "Real Estate": 0.8,
            "Consumer Staples": 1.35,
            "Utilities": 1.4
        }
    },
    "brokers": {
        "moomoo": {
            "enabled": true,
            "account_id": "283445328441899086",
            "_note": "Use the FutuOpenD acc_id (not uni_card_num) so daemon registry matches the account_id stored in quantos-central.db by sync_positions.py"
        }
    },
    "regime_allocations": {
        "_note": "Per-regime sizing and stop factors, read by shared.market_pulse.get_regime_factors() (this is stock_scorer's own block, not Dynamo's \u2014 copy-paste artifact fixed 2026-07-03). aggressive_mult scales per-position concentration (sizing_base_pct \u00d7 mult, sizing_max_pct \u00d7 mult, hard-capped at 2\u00d7). stop_tighten_factor narrows trailing ATR distance.",
        "BULL": {
            "aggressive_mult": 1.5,
            "stop_tighten_factor": 0.6
        },
        "BULL_OVERBOUGHT": {
            "aggressive_mult": 0.5,
            "stop_tighten_factor": 0.4
        },
        "NEUTRAL": {
            "aggressive_mult": 1.5,
            "stop_tighten_factor": 0.6
        },
        "CAUTIOUS": {
            "aggressive_mult": 0.5,
            "stop_tighten_factor": 0.5
        },
        "BEAR": {
            "aggressive_mult": 0.0,
            "stop_tighten_factor": 0.4
        },
        "CRISIS": {
            "aggressive_mult": 0.0,
            "stop_tighten_factor": 0.4
        }
    },
    "industry_regime_allocation": {
        "_note": "Entry-side position-size multiplier by shared.industry_rotation industry pulse_tier. BULL_EXTENDED backtested 2026-07-02 (587 tickers, 5y) at full 1.0x vs the old 0.5x reduction \u2014 it outperforms plain BULL on both return and tail risk, so reducing its size was working against the data. NEUTRAL is still scaled down (not full-allowed). CORRECTING/SOLD/OVERSOLD stay a hard block.",
        "BULL": 1.0,
        "BULL_EXTENDED": 1.0,
        "NEUTRAL": 0.5,
        "CORRECTING": 0.0,
        "SOLD": 0.0,
        "OVERSOLD": 0.0
    }
}

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