API Response Caching

Testing Approach

Testing api response caching includes unit tests for signal logic, integration tests for exchange interaction, and backtests against historical data with realistic slippage modeling.

Production Notes

In production, api response caching requires monitoring for API rate limits, database connection pooling, log rotation, alert thresholds, and automated restart procedures. Document runbooks for incident response.

Performance Metrics

Key metrics include Sharpe ratio, maximum drawdown, win rate, profit factor, and average trade duration. Compare against baseline strategies and adjust parameters based on out-of-sample results.

Configuration Example

Configuration for api response caching uses YAML or JSON format. Key parameters include timeframes, signal thresholds, position sizing rules, and risk limits.

# Example configuration for API Response Caching
strategy:
  name: api-response-caching
  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

Implementation

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