Data Quality and Bias

What this unit covers

Learn to recognise survivorship bias and lookahead bias, the two most common ways a backtest or track record can look better than the honest history.

By the end you will be able to

• Explain how survivorship bias hides failures to inflate an average return.
• Explain how lookahead bias uses information unavailable at the time.
• Apply a two-question check before trusting a performance claim.

How it starts: The Top Ten List

1. You open an app showing the top 10 funds of the last decade.
2. One fund shows an average return of 22 percent a year for ten years.
3. How many funds actually started that decade with this one?

Words you will meet

Survivorship bias

When failed or closed investments are missing from a dataset, making the remaining average look better.

Lookahead bias

When a test uses information that was not actually available at the time it would have been used.

In this module: Quantitative Thinking & Backtesting

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