Ratio Trading Strategy

Configuration Example

Configuration for ratio trading strategy uses YAML or JSON format. Key parameters include timeframes, signal thresholds, position sizing rules, and risk limits.

# Example configuration for Ratio Trading Strategy
strategy:
  name: ratio-trading-strategy
  timeframe: 5m
  indicators:
    - rsi
    - ema_fast
    - ema_slow
  entry_conditions:
    - rsi_oversold
    - ema_crossover_bullish
  exit_conditions:
    - rsi_overbought
    - stop_loss_hit
  risk:
    max_position_size: 0.02
    stop_loss_pct: 0.015

Core Concepts

Understanding ratio trading strategy requires familiarity with market microstructure, order flow dynamics, and execution latency. The following sections detail each component.

Implementation

Implementation of ratio trading strategy follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.

Common Issues

Common issues with ratio trading strategy include look-ahead bias in backtesting, overfitting to historical regimes, inadequate handling of exchange downtime, and insufficient logging for debugging.

Code Structure

The code structure separates concerns: data ingestion, signal generation, risk checks, and order submission. This modularity enables testing and reuse across strategies.

# Example configuration for Ratio Trading Strategy
strategy:
  name: ratio-trading-strategy
  timeframe: 5m
  indicators:
    - rsi
    - ema_fast
    - ema_slow
  entry_conditions:
    - rsi_oversold
    - ema_crossover_bullish
  exit_conditions:
    - rsi_overbought
    - stop_loss_hit
  risk:
    max_position_size: 0.02
    stop_loss_pct: 0.015