alpha" title="Alpha — definition">Alpha tells you how much a manager beat their benchmark. IR tells you how efficiently they did it — alpha per unit of active risk taken. That distinction matters for two reasons.
Consider two funds, both beating the Nifty Midcap 150 by 3% per year over five years:
| Fund | Alpha | Tracking Error | IR |
|---|---|---|---|
| A | 3% | 12% | 0.25 |
| B | 3% | 4% | 0.75 |
Same alpha. Fund B achieved it at one-third the active risk. Fund A may have simply concentrated in a handful of stocks that happened to rally — statistically fragile. Fund B is generating consistent, spread-out outperformance — the signature of genuine skill. [1]
$$IR = \frac{\overline{rr}}{TE}$$
where $\overline{rr}$ is the mean active return and $TE$ is its Volatility) — definition">Standard Deviation (Volatility) — definition">standard deviation. This isolates the quality of the active management decision, stripped of the fund's market exposure. The Sharpe Ratio — definition">Sharpe ratio blends both systematic and active risk together; IR looks only at the active layer. [3] [5]
An active fund earns its higher Expense Ratio — definition">expense ratio only if:
$$IR \times TE > \text{fee differential vs. passive}$$
Raw alpha doesn't give you this test cleanly, because it doesn't tell you whether that alpha is reliable or the product of a lucky concentrated bet. [4]
The Fundamental Law says:
$$IR \approx IC \times \sqrt{B}$$
Alpha can be high for one lucky year. A sustained IR above 0.5 over 5+ years implies the manager has genuine information advantage ($IC > 0$) deployed across many independent bets ($B$ is meaningful). A high alpha with low IR is consistent with luck; a sustained IR is not. [6]
Practical rule: Use alpha to know the size of outperformance. Use IR to know whether it's worth paying for. [5]
Apply this → Sort funds by 5-year IR at Explore Funds and cross-check whether the IR × TE clears the fee hurdle for each one.