mirror of
https://github.com/Sabermrddz/QuantCore-FX.git
synced 2026-07-28 02:57:51 +00:00
saber
289 lines
12 KiB
Python
289 lines
12 KiB
Python
"""
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APEX Layer 1 — Configuration and Constants
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This module loads all configuration from the .env file and defines
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all hardcoded constants for the Currency Strength Engine.
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Responsibilities:
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- Load API keys and settings from .env
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- Define the 8 major currencies tracked
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- Define CB inflation targets (hardcoded — only change if CB mandate changes)
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- Define FRED series IDs for interest rates
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- Define scoring weights
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- Define minimum gap threshold for trading
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- Validate configuration on startup
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"""
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import os
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import logging
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from dotenv import load_dotenv
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from pathlib import Path
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# Load .env file from project root
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env_path = Path(__file__).parent / ".env"
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load_dotenv(dotenv_path=env_path)
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# ============================================================================
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# FRED API Configuration
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# ============================================================================
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FRED_API_KEY = os.getenv("FRED_API_KEY", "")
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FRED_BASE_URL = "https://api.stlouisfed.org/fred"
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# ============================================================================
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# Database Configuration
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# ============================================================================
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DB_PATH = os.getenv("DB_PATH", "apex.db")
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# ============================================================================
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# The 8 Major Currencies
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# ============================================================================
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CURRENCIES = ["USD", "EUR", "GBP", "JPY", "AUD", "CAD", "CHF", "NZD"]
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NUM_CURRENCIES = len(CURRENCIES)
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# ============================================================================
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# Central Bank Inflation Targets (%)
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# ============================================================================
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# These are hardcoded constants. They almost never change.
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# If a central bank officially revises its mandate, update it here manually.
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CB_TARGETS = {
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"USD": 2.0, # Federal Reserve
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"EUR": 2.0, # ECB
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"GBP": 2.0, # Bank of England
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"JPY": 2.0, # Bank of Japan
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"AUD": 2.5, # RBA
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"CAD": 2.0, # Bank of Canada
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"CHF": 1.5, # SNB
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"NZD": 2.0, # RBNZ
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}
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# ============================================================================
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# FRED Series IDs for Interest Rates
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# ============================================================================
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# These map each currency to its FRED series ID.
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# If FRED returns an error, the app will fall back to manual entry (see settings).
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FRED_SERIES = {
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"USD": "FEDFUNDS", # US Federal Funds Rate
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"EUR": "ECBDFR", # ECB Deposit Rate
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"GBP": "BOEIR", # Bank of England Interest Rate
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"JPY": "IRSTCI01JPM156N", # Japan Short-Term Interest Rate
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"AUD": "RBATR", # RBA Target Cash Rate
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"CAD": "BOCARR", # Bank of Canada Overnight Rate
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"CHF": "SNBON", # SNB Policy Rate
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"NZD": "RBNZR", # RBNZ Official Cash Rate
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}
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# ============================================================================
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# Scoring Configuration
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# ============================================================================
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WEIGHT_RATE = float(os.getenv("WEIGHT_RATE", 0.50)) # Interest rate diff: 50%
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WEIGHT_CPI = float(os.getenv("WEIGHT_CPI", 0.30)) # CPI deviation: 30%
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WEIGHT_PMI = float(os.getenv("WEIGHT_PMI", 0.20)) # PMI composite: 20%
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# Verify weights sum to 1.0 (with tolerance for floating point precision)
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TOTAL_WEIGHT = WEIGHT_RATE + WEIGHT_CPI + WEIGHT_PMI
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if not (0.99 <= TOTAL_WEIGHT <= 1.01):
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raise ValueError(
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f"Weights must sum to 1.0. "
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f"Current: RATE={WEIGHT_RATE}, CPI={WEIGHT_CPI}, PMI={WEIGHT_PMI} "
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f"(total={TOTAL_WEIGHT})"
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)
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# ============================================================================
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# Trading Rules
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# ============================================================================
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MIN_GAP_TO_TRADE = float(os.getenv("MIN_GAP", 20)) # Minimum 20-point gap
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# Gap threshold tiers (used for UI display and Layer 2+ position sizing)
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GAP_THRESHOLDS = {
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"no_trade": 20, # Gap < 20: NO TRADE
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"weak": 40, # Gap 20-40: Weak signal, max 0.5%
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"standard": 60, # Gap 40-60: Standard signal, max 1.0%
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"strong": float("inf") # Gap > 60: Strong signal (Layer 5+ for full sizing)
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}
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# ============================================================================
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# Auto-fetch Settings
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# ============================================================================
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AUTO_FETCH_RATES_ON_STARTUP = os.getenv("AUTO_FETCH_RATES_ON_STARTUP", "true").lower() == "true"
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FRED_FETCH_TIMEOUT = 10 # seconds
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# ============================================================================
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# Data Validation Rules
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# ============================================================================
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RATE_MIN = -5.0 # Some CBs have negative rates
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RATE_MAX = 20.0 # Reasonable upper bound
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CPI_MIN = float(os.getenv("CPI_MIN", -5.0))
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CPI_MAX = float(os.getenv("CPI_MAX", 10.0))
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PMI_MIN = float(os.getenv("PMI_MIN", 0.0))
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PMI_MAX = float(os.getenv("PMI_MAX", 100.0))
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# ============================================================================
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# Database Settings
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# ============================================================================
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DB_AUTO_CREATE = True # Automatically create schema if DB doesn't exist
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DB_TIMEOUT = 5 # Connection timeout in seconds
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# ============================================================================
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# Validation Function
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# ============================================================================
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def validate_config():
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"""
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Validate configuration on startup.
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Raises ValueError if critical settings are missing or invalid.
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"""
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errors = []
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if not FRED_API_KEY:
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errors.append(
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"FRED_API_KEY not set in .env file. "
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"Get a free key from fred.stlouisfed.org and add to .env"
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)
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if not DB_PATH:
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errors.append("DB_PATH not configured in .env or config.py")
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for currency in CURRENCIES:
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if currency not in CB_TARGETS:
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errors.append(f"Missing CB target for {currency}")
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if currency not in FRED_SERIES:
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errors.append(f"Missing FRED series ID for {currency}")
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if errors:
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raise ValueError(
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"Configuration validation failed:\n" + "\n".join(f" - {e}" for e in errors)
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)
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# ============================================================================
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# Debug Mode
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# ============================================================================
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DEBUG = os.getenv("DEBUG", "false").lower() == "true"
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# ============================================================================
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# Logging Configuration (Phase 5)
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# ============================================================================
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LOG_LEVEL = logging.DEBUG if DEBUG else logging.INFO
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LOG_FORMAT = "%(asctime)s [%(levelname)s] %(name)s: %(message)s"
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LOG_FILE = os.getenv("LOG_FILE", "apex.log")
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logging.basicConfig(
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level=LOG_LEVEL,
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format=LOG_FORMAT,
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handlers=[
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logging.FileHandler(LOG_FILE),
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logging.StreamHandler(),
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],
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)
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logger = logging.getLogger("apex")
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# ============================================================================
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# UI Configuration
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# ============================================================================
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APP_TITLE = "APEX — Currency Strength Engine"
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WINDOW_WIDTH = 1400
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WINDOW_HEIGHT = 850
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TAB_NAMES = {
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"dashboard": "📊 Dashboard",
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"entry": "📝 Data Entry",
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"layer2": "📈 Layer 2 (Technical)",
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"confluence": "🎯 Confluence Signals",
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"history": "📜 History",
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"settings": "⚙️ Settings"
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}
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# Currency emojis for UI
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CURRENCY_EMOJIS = {
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"USD": "🇺🇸",
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"EUR": "🇪🇺",
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"GBP": "🇬🇧",
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"JPY": "🇯🇵",
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"AUD": "🇦🇺",
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"CAD": "🇨🇦",
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"CHF": "🇨🇭",
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"NZD": "🇳🇿",
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}
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# ============================================================================
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# LAYER 2 — Technical Analysis Configuration
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# ============================================================================
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# MetaTrader 5 (local terminal, no API key needed)
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# Symbol suffix varies by broker (e.g., .m for OANDA MT5)
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MT5_SYMBOL_SUFFIX = os.getenv("MT5_SYMBOL_SUFFIX", "")
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# Technical Analysis Settings
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Z_SCORE_THRESHOLD = float(os.getenv("Z_SCORE_THRESHOLD", 2.0)) # Overbought/oversold level (legacy/macro)
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SCALP_Z_SCORE_THRESHOLD = float(os.getenv("SCALP_Z_SCORE_THRESHOLD", 1.5)) # Intraday threshold (more sensitive)
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SCALP_MIN_GAP_TO_TRADE = float(os.getenv("SCALP_MIN_GAP", 2.0)) # Intraday min gap (sigma units)
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# Multi-timeframe configuration (short lookbacks for scalping)
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TIMEFRAMES = {
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"M5": {"interval": "5min", "bars": 48, "label": "5 min"},
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"M15": {"interval": "15min", "bars": 16, "label": "15 min"},
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"H1": {"interval": "1h", "bars": 12, "label": "1 hour"},
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"H4": {"interval": "4h", "bars": 6, "label": "4 hour"},
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}
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DEFAULT_TIMEFRAME = os.getenv("DEFAULT_TIMEFRAME", "M5")
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# Historical bar config (backward compat)
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BAR_TIMEFRAME = os.getenv("BAR_TIMEFRAME", "M5")
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BAR_LOOKBACK_HOURS = int(os.getenv("BAR_LOOKBACK_HOURS", 48))
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HISTORICAL_POLL_INTERVAL = int(os.getenv("HISTORICAL_POLL_INTERVAL", 300)) # 5 min in seconds
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# SL/TP based on ATR
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SL_ATR_PERIOD = 14
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SL_ATR_MULTIPLIER = float(os.getenv("SL_ATR_MULTIPLIER", "2.0"))
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TRADE_RR_RATIO = float(os.getenv("TRADE_RR_RATIO", "1.4"))
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# Session Detection
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SESSION_TOKYO_OPEN = 0 # 00:00 UTC
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SESSION_TOKYO_CLOSE = 8 # 08:00 UTC
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SESSION_LONDON_OPEN = 7 # 07:00 UTC
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SESSION_LONDON_CLOSE = 16 # 16:00 UTC
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SESSION_NEWYORK_OPEN = 13 # 13:00 UTC
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SESSION_NEWYORK_CLOSE = 21# 21:00 UTC
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# ============================================================================
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# Confluence Layer Weights (Scalper Profile)
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# ============================================================================
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# Effective weight distribution for signal display:
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# - Market Structure + Order Flow (Currency Strength Matrix / Z-scores): ~65%
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# - Currency Power Matrix (Session SRV + momentum): ~25%
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# - Macro / Fundamental Backdrop (Layer 1 scorer, advisory only): ~10%
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#
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# The macro layer is DISPLAY ONLY — it never blocks or vetoes a trade signal.
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# Currency Power Matrix refers to CurrencyStrengthMatrix (this engine).
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# ============================================================================
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CONFLUENCE_ENABLED = os.getenv("CONFLUENCE_ENABLED", "true").lower() == "true"
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MIN_CONFLUENCE_STRENGTH = float(os.getenv("MIN_CONFLUENCE_STRENGTH", 60.0)) # 60% confidence threshold
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# Risk Management
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ACCOUNT_BALANCE = float(os.getenv("ACCOUNT_BALANCE", 10000.0)) # Starting balance
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RISK_PER_TRADE = float(os.getenv("RISK_PER_TRADE", 0.01)) # 1% per trade
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MAX_PORTFOLIO_LEVERAGE = float(os.getenv("MAX_PORTFOLIO_LEVERAGE", 2.0)) # Max 2:1 leverage
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USE_GRID_HEDGING = os.getenv("USE_GRID_HEDGING", "true").lower() == "true"
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GRID_LEVELS = int(os.getenv("GRID_LEVELS", 3)) # Number of hedging levels
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# Live Execution (Phase 4) — OFF by default
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LIVE_TRADING_ENABLED = os.getenv("LIVE_TRADING_ENABLED", "false").lower() == "true"
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MAX_DAILY_LOSS_PCT = float(os.getenv("MAX_DAILY_LOSS_PCT", 0.05))
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MAX_BASKET_EXPOSURE_PCT = float(os.getenv("MAX_BASKET_EXPOSURE_PCT", 0.20))
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if DEBUG:
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print("[CONFIG] Debug mode enabled")
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print(f"[CONFIG] FRED API Key: {FRED_API_KEY[:10]}..." if FRED_API_KEY else "[CONFIG] FRED API Key: NOT SET")
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print(f"[CONFIG] MT5 symbol suffix: '{MT5_SYMBOL_SUFFIX}'")
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print(f"[CONFIG] Database: {DB_PATH}")
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print(f"[CONFIG] Weights: Rate={WEIGHT_RATE}, CPI={WEIGHT_CPI}, PMI={WEIGHT_PMI}")
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print(f"[CONFIG] Min gap to trade: {MIN_GAP_TO_TRADE}")
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print(f"[CONFIG] Z-score threshold: {Z_SCORE_THRESHOLD}")
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print(f"[CONFIG] Confluence enabled: {CONFLUENCE_ENABLED}")
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# Call validation on import (fail early if config is broken)
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try:
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validate_config()
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except ValueError as e:
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print(f"[ERROR] Configuration validation failed:\n{e}")
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raise
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