Assumptions, Costs, and Overfitting

What this unit covers

Understand how ignored costs and slippage, and overfitting a rule too closely to past data, both quietly inflate how good a strategy looks.

By the end you will be able to

• Explain how ignoring real trading costs and slippage inflates a backtest's returns.
• Explain why a rule tuned tightly to past data can fail on new data.
• Identify two hidden assumptions worth questioning before trusting a backtest.

How it starts: A Report Too Good to Question

1. A friend sends you a strategy report with a smooth, rising ten-year return line.
2. You have a few minutes before you decide whether to put money behind it.
3. Why does a curve this clean make you hesitate instead of feel reassured?

Words you will meet

Backtest

A simulation of how a trading rule would have performed on past price data.

Slippage

The gap between the price you expected and the price you actually got when your order filled.

Overfitting

Tuning a rule so tightly to one stretch of past data that it stops working on new data.

In this module: Quantitative Thinking & Backtesting

1. Probability and Basic Statistics
2. Data Quality and Bias
3. Assumptions, Costs, and Overfitting (this unit)
4. Walk-Forward Thinking and Performance Interpretation