Portfolio alpha, without the shortcuts.

Three different questions

Raw return asks how a value changed under a defined return convention. Simple excess return compares that return with a chosen benchmark over the same period. Model-based alpha asks what remains relative to a specified model of expected or explained return.

The example panels below show cumulative returns and simple benchmark excess return. They deliberately do not label the difference “risk-adjusted alpha.” Read what stock market alpha measures for the model-based distinction.

Make the benchmark policy visible

A fair comparison starts with the portfolio’s intended opportunity set and constraints. Document why the reference is relevant, how it is rebalanced, and whether its return includes distributions. Align the portfolio’s cost and currency treatment before interpreting differences.

A benchmark chosen after seeing the outcome creates a selection problem. The portfolio benchmarking guide shows how to define the comparison before reviewing performance.

The route matters as much as the endpoint

The same cumulative return can arrive through very different paths. Drawdown captures a decline from an observed peak; volatility describes dispersion under a specified return and sampling convention. Neither summarizes every form of risk.

Use risk and performance to examine what is measured and what is omitted. The sample drawdowns are calculated only at the displayed intervals, not from daily or intraday observations that do not exist in the dataset.

Treat an estimate as an estimate

An alpha estimate depends on the model, time period, observations, and assumptions. It does not by itself establish causation, persistence, or a transferable trading advantage. Investigate uncertainty and stability rather than treating one number as a verdict.

The alpha versus beta article provides a practical reading framework. All dashboard paths on this site are invented examples, not a portfolio track record.