ParallelLLC/algorithmic_trading

1# Configuration file for the agentic AI trading system2data_source:3  type: 'yahoo'4  path: 'data/market_data.csv'5 6trading:7  symbol: 'AAPL'8  timeframe: '1d'9  capital: 10000010 11risk:12  max_position: 10013  max_drawdown: 0.0514 15execution:16  broker_api: 'paper'  # Options: 'paper', 'alpaca_paper', 'alpaca_live'17  order_size: 1018  delay_ms: 10019  success_rate: 0.9520 21# Alpaca configuration22alpaca:23  api_key: ''  # Set via environment variable ALPACA_API_KEY24  secret_key: ''  # Set via environment variable ALPACA_SECRET_KEY25  paper_trading: true  # Use paper trading by default26  base_url: 'https://paper-api.alpaca.markets'  # Paper trading URL27  live_url: 'https://api.alpaca.markets'  # Live trading URL28  data_url: 'https://data.alpaca.markets'  # Market data URL29  websocket_url: 'wss://stream.data.alpaca.markets/v2/iex'  # WebSocket URL30  account_type: 'paper'  # 'paper' or 'live'31 32# Yahoo Finance (default ingest). Unofficial API, typically delayed; 1m lookback is ~7 days.33# Unofficial API, typically delayed; 1m lookback is ~7 days.34yahoo:35  poll_interval_seconds: 6036  # Keep true. With auto_adjust off, Yahoo returns raw Close and every stock37  # split reads as a crash (NVDA's June 2024 10:1 becomes a -90% bar).38  auto_adjust: true39  # Yahoo returns the still-forming period as an ordinary row. Emitting it would40  # trade on a close that has not happened yet.41  emit_incomplete_bars: false42  max_backoff_seconds: 90043  start_date: '2024-01-01'44  end_date: '2026-12-31'45 46# Synthetic data generation settings47synthetic_data:48  base_price: 150.049  volatility: 0.0250  trend: 0.00151  noise_level: 0.00552  generate_data: true53  data_path: 'data/synthetic_market_data.csv'54 55# Logging configuration56logging:57  log_level: 'INFO'58  log_dir: 'logs'59  enable_console: true60  enable_file: true61  max_file_size_mb: 1062  backup_count: 563 64# FinRL configuration65finrl:66  algorithm: 'PPO'  # PPO, A2C, DDPG, TD367  learning_rate: 0.000368  batch_size: 6469  buffer_size: 100000070  learning_starts: 10071  gamma: 0.9972  tau: 0.00573  train_freq: 174  gradient_steps: 175  target_update_interval: 176  exploration_fraction: 0.177  exploration_initial_eps: 1.078  exploration_final_eps: 0.0579  max_grad_norm: 10.080  verbose: 181  tensorboard_log: 'logs/finrl_tensorboard'82  training:83    total_timesteps: 10000084    eval_freq: 1000085    save_best_model: true86    model_save_path: 'models/finrl_best/'87  inference:88    use_trained_model: false89    model_path: 'models/finrl_best/best_model'90