Market Making Spread Optimizer

What this market-making coding problem tests

This is an easy Python coding problem that combines basic state management with financial reasoning. It asks you to simulate a market maker's profit-and-loss calculation under inventory constraints—a fundamental building block in any trading platform or risk system.

The problem rewards careful implementation of the accept/reject logic, correct tracking of cash and inventory across trades, and proper handling of the liquidation step at the end. It is representative of the kind of practical simulation work that quantitative trading firms use to backtest and validate strategies. The key skills are translating a clear specification into code, managing multiple state variables, and understanding how inventory limits enforce risk control.

• Stateful simulation loops
• Conditional logic and trade filtering
• Cash-and-carry accounting
• Rounding and output formatting