Sensitivity Analysis

Overview Code Structure Risk Considerations Testing Approach Core Concepts

Overview

This guide covers sensitivity analysis implementation in automated trading systems. The approach combines established patterns with operational considerations drawn from production deployments.

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 Sensitivity Analysis
strategy:
  name: sensitivity-analysis
  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

Risk Considerations

Risk management for sensitivity analysis addresses position limits, stop loss placement, correlation exposure, and worst-case drawdown scenarios. Regular monitoring prevents drift from intended behavior.

Important: Always validate sensitivity analysis logic on out-of-sample data before live deployment. Paper trading reveals execution issues that backtests miss.

Testing Approach

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

Core Concepts

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