MaverickMCP

""" Configuration settings for the Tiingo data loader. This file contains configuration options that can be customized for different loading scenarios and environments. """ import os from dataclasses import dataclass from typing import Any @dataclass class TiingoConfig: """Configuration for Tiingo data loader.""" # API Configuration rate_limit_per_hour: int = 2400 # Tiingo free tier limit max_retries: int = 3 retry_backoff_multiplier: float = 2.0 request_timeout: int = 30 # Concurrent Processing max_concurrent_requests: int = 5 default_batch_size: int = 50 # Data Loading Defaults default_years_of_data: int = 2 min_stock_price: float = 5.0 # Minimum stock price for screening min_volume: int = 100000 # Minimum daily volume # Technical Indicators rsi_period: int = 14 sma_periods: list[int] = None ema_periods: list[int] = None macd_fast: int = 12 macd_slow: int = 26 macd_signal: int = 9 bollinger_period: int = 20 bollinger_std: float = 2.0 atr_period: int = 14 adx_period: int = 14 stoch_k_period: int = 14 stoch_d_period: int = 3 stoch_smooth: int = 3 # Screening Criteria maverick_min_momentum_score: float = 70.0 maverick_min_volume: int = 500000 bear_max_momentum_score: float = 30.0 bear_min_volume: int = 300000 supply_demand_min_momentum_score: float = 60.0 supply_demand_min_volume: int = 400000 # Progress Tracking checkpoint_interval: int = 10 # Save checkpoint every N symbols def __post_init__(self): if self.sma_periods is None: self.sma_periods = [20, 50, 150, 200] if self.ema_periods is None: self.ema_periods = [21] # Market sectors for filtering MARKET_SECTORS = { "technology": [ "AAPL", "MSFT", "GOOGL", "AMZN", "META", "NVDA", "ADBE", "CRM", "INTC", "AMD", "ORCL", "IBM", "NFLX", "CSCO", "ACN", "TXN", "QCOM", "NOW", "SNPS", "LRCX", ], "healthcare": [ "UNH", "JNJ", "PFE", "ABBV", "TMO", "ABT", "BMY", "MDT", "GILD", "REGN", "ISRG", "ZTS", "BSX", "BDX", "SYK", "EL", "CVS", "ANTM", "CI", "HUM", ], "financial": [ "JPM", "BAC", "WFC", "GS", "MS", "AXP", "BLK", "C", "USB", "PNC", "SCHW", "CB", "AON", "ICE", "CME", "SPGI", "MCO", "TRV", "ALL", "AIG", ], "consumer_discretionary": [ "HD", "WMT", "DIS", "NKE", "COST", "TJX", "SBUX", "TGT", "MAR", "GM", "F", "CCL", "RCL", "NCLH", "TSLA", "ETSY", "EBAY", "BKNG", "EXPE", "YUM", ], "energy": [ "CVX", "EOG", "SLB", "COP", "PSX", "VLO", "MPC", "PXD", "KMI", "OXY", "WMB", "HAL", "BKR", "DVN", "FANG", "APA", "MRO", "XOM", "CTRA", "OKE", ], "industrials": [ "CAT", "BA", "HON", "UPS", "GE", "MMM", "ITW", "DE", "EMR", "CSX", "NSC", "FDX", "LMT", "RTX", "NOC", "GD", "WM", "RSG", "PCAR", "IR", ], } # Trading strategy configurations TRADING_STRATEGIES = { "momentum": { "min_momentum_score": 80, "min_price_above_sma50": True, "min_price_above_sma200": True, "min_volume_ratio": 1.2, "max_rsi": 80, "required_indicators": ["RSI_14", "SMA_50", "SMA_200", "MOMENTUM_SCORE"], }, "value": { "max_pe_ratio": 20, "min_dividend_yield": 2.0, "max_price_to_book": 3.0, "min_market_cap": 1_000_000_000, # $1B "required_fundamentals": ["pe_ratio", "dividend_yield", "price_to_book"], }, "breakout": { "min_bb_squeeze_days": 20, "min_consolidation_days": 30, "min_volume_breakout_ratio": 2.0, "min_price_breakout_pct": 0.05, # 5% "required_indicators": ["BB_UPPER", "BB_LOWER", "VOLUME", "ATR_14"], }, "mean_reversion": { "max_rsi": 30, # Oversold "min_bb_position": -2.0, # Below lower Bollinger Band "max_distance_from_sma50": -0.10, # 10% below SMA50 "min_momentum_score": 40, # Not completely broken "required_indicators": ["RSI_14", "BB_LOWER", "SMA_50", "MOMENTUM_SCORE"], }, } # Symbol lists for different markets/exchanges SYMBOL_LISTS = { "sp500_top_100": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA", "META", "NVDA", "BRK.B", "UNH", "JNJ", "V", "PG", "JPM", "HD", "CVX", "MA", "PFE", "ABBV", "BAC", "KO", "AVGO", "PEP", "TMO", "COST", "WMT", "DIS", "ABT", "ACN", "NFLX", "ADBE", "CRM", "VZ", "DHR", "INTC", "NKE", "T", "TXN", "BMY", "QCOM", "PM", "UPS", "HON", "ORCL", "WFC", "LOW", "LIN", "AMD", "SBUX", "IBM", "GE", "CAT", "MDT", "BA", "AXP", "GILD", "RTX", "GS", "BLK", "MMM", "CVS", "ISRG", "NOW", "AMT", "SPGI", "PLD", "SYK", "TJX", "MDLZ", "ZTS", "MO", "CB", "CI", "PYPL", "SO", "EL", "DE", "REGN", "CCI", "USB", "BSX", "DUK", "AON", "CSX", "CL", "ITW", "PNC", "FCX", "SCHW", "EMR", "NSC", "GM", "FDX", "MU", "BDX", "TGT", "EOG", "SLB", "ICE", "EQIX", "APD", ], "nasdaq_100": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA", "META", "NVDA", "ADBE", "NFLX", "CRM", "INTC", "AMD", "QCOM", "TXN", "AVGO", "ORCL", "CSCO", "PEP", "COST", "SBUX", "PYPL", "GILD", "REGN", "ISRG", "BKNG", "ZM", "DOCU", "ZOOM", "DXCM", "BIIB", ], "dow_30": [ "AAPL", "MSFT", "UNH", "GS", "HD", "CAT", "AMGN", "MCD", "V", "BA", "TRV", "AXP", "JPM", "IBM", "PG", "CVX", "NKE", "JNJ", "WMT", "DIS", "MMM", "DOW", "KO", "CSCO", "HON", "CRM", "VZ", "INTC", "WBA", "MRK", ], "growth_stocks": [ "TSLA", "NVDA", "AMD", "NFLX", "CRM", "ADBE", "SNOW", "PLTR", "SQ", "ROKU", "ZOOM", "DOCU", "TWLO", "OKTA", "DDOG", "CRWD", "NET", "FSLY", "TTD", "TEAM", ], "dividend_stocks": [ "JNJ", "PG", "KO", "PEP", "WMT", "HD", "ABT", "MCD", "VZ", "T", "CVX", "XOM", "PM", "MO", "MMM", "CAT", "IBM", "GE", "BA", "DIS", ], } # Environment-specific configurations def get_config_for_environment(env: str = None) -> TiingoConfig: """Get configuration based on environment.""" env = env or os.getenv("ENVIRONMENT", "development") if env == "production": return TiingoConfig( max_concurrent_requests=10, # Higher concurrency in production default_batch_size=100, # Larger batches rate_limit_per_hour=5000, # Assuming paid Tiingo plan checkpoint_interval=5, # More frequent checkpoints ) elif env == "testing": return TiingoConfig( max_concurrent_requests=2, # Lower concurrency for tests default_batch_size=10, # Smaller batches default_years_of_data=1, # Less data for faster tests checkpoint_interval=2, # Frequent checkpoints for testing ) else: # development return TiingoConfig() # Default configuration # Screening algorithm configurations SCREENING_CONFIGS = { "maverick_momentum": { "price_above_ema21": True, "ema21_above_sma50": True, "sma50_above_sma200": True, "min_momentum_score": 70, "min_volume": 500000, "min_price": 10.0, "scoring_weights": { "price_above_ema21": 2, "ema21_above_sma50": 2, "sma50_above_sma200": 3, "momentum_score_80plus": 3, "momentum_score_70plus": 2, "volume_above_avg": 1, }, }, "bear_market": { "price_below_ema21": True, "ema21_below_sma50": True, "max_momentum_score": 30, "min_volume": 300000, "min_price": 5.0, "scoring_weights": { "price_below_ema21": 2, "ema21_below_sma50": 2, "momentum_score_below_20": 3, "momentum_score_below_30": 2, "high_volume_decline": 2, }, }, "supply_demand": { "price_above_sma50": True, "sma50_above_sma200": True, "min_momentum_score": 60, "min_volume": 400000, "min_price": 8.0, "accumulation_signals": [ "tight_consolidation", "volume_dry_up", "relative_strength", "institutional_buying", ], }, } # Database optimization settings DATABASE_CONFIG = { "batch_insert_size": 1000, "connection_pool_size": 20, "statement_timeout": 30000, # 30 seconds "bulk_operations": True, "indexes_to_create": [ "idx_price_cache_symbol_date", "idx_technical_cache_symbol_indicator", "idx_maverick_stocks_score", "idx_stocks_sector_industry", ], } # Logging configuration LOGGING_CONFIG = { "version": 1, "disable_existing_loggers": False, "formatters": { "detailed": { "format": "%(asctime)s - %(name)s - %(levelname)s - %(funcName)s:%(lineno)d - %(message)s" }, "simple": {"format": "%(asctime)s - %(levelname)s - %(message)s"}, }, "handlers": { "console": { "class": "logging.StreamHandler", "level": "INFO", "formatter": "simple", "stream": "ext://sys.stdout", }, "file": { "class": "logging.FileHandler", "level": "DEBUG", "formatter": "detailed", "filename": "tiingo_loader.log", "mode": "a", }, "error_file": { "class": "logging.FileHandler", "level": "ERROR", "formatter": "detailed", "filename": "tiingo_errors.log", "mode": "a", }, }, "loggers": { "tiingo_data_loader": { "level": "DEBUG", "handlers": ["console", "file", "error_file"], "propagate": False, } }, } def get_symbols_for_strategy(strategy: str) -> list[str]: """Get symbol list based on trading strategy.""" if strategy in SYMBOL_LISTS: return SYMBOL_LISTS[strategy] elif strategy in MARKET_SECTORS: return MARKET_SECTORS[strategy] else: return SYMBOL_LISTS["sp500_top_100"] # Default def get_screening_config(screen_type: str) -> dict[str, Any]: """Get screening configuration for specified type.""" return SCREENING_CONFIGS.get(screen_type, SCREENING_CONFIGS["maverick_momentum"]) # Default configuration instance default_config = get_config_for_environment()