How the Information Ratio Calculator works
The Information Ratio (IR) is a standard risk-adjusted performance measure used to judge whether an actively managed portfolio's excess return over its benchmark is being earned efficiently, or is just noise. It divides the portfolio's annualized active return (portfolio return minus benchmark return) by its annualized tracking error (the standard deviation of that excess return). A higher Information Ratio means a manager is generating more active return per unit of active risk taken relative to the benchmark.
The formula
For a series of periodic returns, first compute the excess return in each period: excess return = portfolio return − benchmark return. From that series, this calculator asks for two summary statistics instead of a full return history:
- Average excess return per period — the mean of the periodic excess returns.
- Standard deviation of excess return per period — the dispersion of those excess returns, i.e. the periodic tracking error.
The per-period Information Ratio is IR = average excess return / standard deviation of excess return. Because most Information Ratios are reported on an annual basis, the calculator annualizes each component using the number of return periods per year (N): annualized active return = average excess return × N; annualized tracking error = standard deviation × √N; and annualized IR = periodic IR × √N (equivalently, annualized active return ÷ annualized tracking error).
Worked example
Suppose a fund has averaged a 0.50% monthly excess return over its benchmark with a monthly standard deviation of that excess return of 1.20%, measured over 36 months. The periodic IR is 0.50 / 1.20 ≈ 0.417. Annualizing with N = 12: active return ≈ 0.50% × 12 = 6.0%, tracking error ≈ 1.20% × √12 ≈ 4.16%, and the annualized Information Ratio ≈ 0.417 × √12 ≈ 1.44 (equivalently 6.0% / 4.16%). Under the Grinold & Kahn rule of thumb, an IR near 1.4 would be considered exceptional and unusually persistent if it held up over a longer track record.
Interpreting the Information Ratio
A widely cited scale from Richard Grinold and Ronald Kahn's Active Portfolio Management treats an IR of 0.5 as "good," 0.75 as "very good," and 1.0 as "exceptional" — genuinely sustaining an IR above 1.0 over many years is rare among active managers. An IR near or below zero means the manager's active bets have not reliably added value after accounting for the risk taken relative to the benchmark. Because IR is a ratio of a mean to a standard deviation, it also behaves like a signal-to-noise measure: the calculator's approximate t-statistic (periodic IR × √(number of periods observed)) gives a rough sense of whether the average excess return is statistically distinguishable from zero — as a common rule of thumb, a t-statistic beyond roughly ±2 is often treated as suggestive of significance at conventional confidence levels, though more observations are generally needed to draw firm conclusions.
What moves the Information Ratio
- Consistency of outperformance: a smaller, steadier excess return can produce a higher IR than a larger but erratic one, because tracking error penalizes volatility in the active return.
- Benchmark choice: IR is only meaningful relative to a benchmark that reflects the portfolio's actual investment mandate; an ill-fitting benchmark distorts both the active return and the tracking error.
- Sample length: a short return history can produce an extreme IR by chance. The t-statistic column exists precisely to flag when a sample is too short to trust the ratio at face value.
Assumptions and limits
This calculator assumes the excess returns you summarize are drawn from a reasonably stable process and that the standard deviation you enter already reflects the return frequency selected. It does not account for fees, taxes, benchmark misfit, or survivorship bias in the underlying track record, and it is not investment advice — it is a standard, transparent computation of a widely used performance-analysis ratio.