trading cost reality simulator

The problem

Most backtests look great on paper because they ignore the friction of live markets. Developers and traders often find that a profitable "alpha" disappears once commissions, slippage, and bid/ask spreads are factored in.

What it does

• Calculates total transaction costs by combining commissions, bid/ask spreads, and slippage estimates.
• Adjusts trade-by-trade logs or cumulative equity curves to reflect net performance.
• Recomputes critical performance metrics like Sharpe ratio, CAGR, and max drawdown after friction.
• Conducts sensitivity analysis across low, medium, and high-cost scenarios to find the breaking point of a strategy.

Why this beats prompting it yourself

This skill applies standardized institutional-grade cost assumptions for different asset classes (Forex, Crypto, Options, Equities) out of the box. It prevents the common "optimism bias" that occurs when users manually prompt for cost analysis without accounting for market impact or two-sided execution fees.

Use cases

• Sanity check a new strategy's viability before deploying capital.
• Determine the maximum allowable turnover for a high-frequency signal.
• Compare net returns across different brokers or fee schedules.
• Analyze if a crypto strategy survives the high basis point costs of specific exchanges.

Known limitations

Does not account for complex tax implications like wash sales or specific regional capital gains rules.