config.yaml

# TiMi System Configuration

# Mode: backtest, paper, live
mode: paper

# LLM Configuration
llm:
  # Semantic Analysis - for macro/micro strategy analysis
  semantic:
    provider: openai  # openai, anthropic
    model: gpt-5-2025-08-07
    # Alternative: claude-sonnet-4-5-20250514 (anthropic)
    temperature: 0.7
    max_tokens: 4000

  # Code Programming - for bot evolution
  code:
    provider: openai
    model: gpt-5-pro-2025-10-06
    # Alternative: claude-sonnet-4-5-20250514 (anthropic) - best for coding
    temperature: 0.3
    max_tokens: 8000

  # Mathematical Reasoning - for parameter optimization
  reasoning:
    provider: openai
    model: gpt-5-pro-2025-10-06
    # Alternative: claude-opus-4-1-20250514 (anthropic) - specialized reasoning
    temperature: 0.2
    max_tokens: 4000

# Exchange Configuration
exchange:
  primary: binance
  testnet: true  # Use testnet for testing

  binance:
    rate_limit: 1200  # requests per minute
    timeout: 30000    # milliseconds

  cme:
    enabled: false

# Trading Pairs Configuration
trading_pairs:
  # Mainstream coins
  mainstream:
    - BTC/USDT
    - ETH/USDT
    - BNB/USDT

  # Altcoins (higher volatility)
  altcoins:
    - SOL/USDT
    - AVAX/USDT
    - MATIC/USDT

  # Active pairs (what to trade)
  active: []  # Will be populated by strategy

# Strategy Parameters (Algorithm 1 from paper)
strategy:
  # T1: Execution intervals (minutes)
  execution_interval: 1

  # T2: Look-back period for volatility calculation (minutes)
  lookback_period: 60

  # Volume requirement (minimum 24h volume in USD)
  min_volume: 1000000

  # Φreq: Minimum volatility requirement (%)
  min_volatility: 0.5

  # A: Capital allocation per pair (USD)
  capital_per_pair: 100

  # MP: Price distribution matrix (exponents for grid levels)
  price_distribution: [0.5, 0.75, 1.0, 1.25, 1.5, 2.0, 2.5]

  # MQ: Quantity distribution matrix (proportions)
  quantity_distribution: [0.2, 0.2, 0.2, 0.15, 0.15, 0.05, 0.05]

  # H: Profit/loss thresholds (multiples of volatility)
  profit_loss_thresholds: [1.5, 2.0, 3.0, 5.0]

  # Scaling coefficients
  market_cap_coefficient: 1.0
  funding_rate_coefficient: 1.0
  entry_coefficient: 0.8

# Risk Management
risk:
  # Maximum drawdown before emergency stop (%)
  max_drawdown: 20

  # Maximum position size as % of capital
  max_position_pct: 10

  # Maximum number of concurrent positions
  max_concurrent_positions: 5

  # Stop loss per position (%)
  stop_loss_pct: 5

  # Price deviation check (%)
  max_price_deviation: 2

  # Position size divisor (lambda from paper)
  position_size_divisor: 10

# Optimization Stage Configuration
optimization:
  enabled: true

  # Simulation settings
  simulation:
    # Historical data period for backtesting
    historical_days: 90

    # Number of optimization cycles
    max_cycles: 5

    # Minimum performance improvement to continue
    min_improvement: 0.05

  # Feedback collection
  feedback:
    # Collect every N minutes during simulation
    collection_interval: 60

    # Metrics to track
    metrics:
      - annual_return
      - sharpe_ratio
      - max_drawdown
      - win_rate
      - profit_factor

# Agent Configuration
agents:
  macro_analysis:
    enabled: true
    # Technical indicators to analyze
    indicators:
      - SMA
      - EMA
      - RSI
      - MACD
      - Bollinger_Bands
      - ATR
      - Volume

    # Time windows for analysis (in days)
    time_windows: [1, 7, 30, 90]

  strategy_adaptation:
    enabled: true
    # Pair-specific factors to consider
    factors:
      - historical_volatility
      - liquidity_depth
      - correlation_with_btc
      - funding_rate_history

  bot_evolution:
    enabled: true
    # Programming laws enforcement
    enforce_laws: true

    # Code quality checks
    quality_checks:
      - syntax_validation
      - security_scan
      - performance_check

  feedback_reflection:
    enabled: true
    # Optimization approach
    method: linear_programming

    # Hierarchical levels
    optimization_levels:
      - parameter
      - function
      - strategy

# Monitoring and Logging
monitoring:
  enabled: true
  port: 8000

  # Metrics to expose
  metrics:
    - active_positions
    - total_pnl
    - win_rate
    - order_latency
    - api_errors

  # Alert thresholds
  alerts:
    drawdown_threshold: 10  # Alert if drawdown exceeds %
    error_rate_threshold: 5  # Alert if errors exceed N per minute

logging:
  level: INFO
  format: json

  # Log to file
  file:
    enabled: true
    path: logs/timi.log
    max_size_mb: 100
    backup_count: 5

  # Log to console
  console:
    enabled: true

# Database
database:
  # Store trading history, feedback, etc.
  type: sqlite
  path: data/timi.db

  # Tables to maintain
  tables:
    - trades
    - positions
    - feedback
    - bot_versions
    - optimization_history

# Backtesting
backtest:
  # Data source
  data_source: binance

  # Initial capital
  initial_capital: 10000

  # Commission rate
  commission: 0.001  # 0.1%

  # Slippage model
  slippage: 0.0005  # 0.05%