Information Ratio - Sharpe Ratio for Benchmark-Relative Strategies

By EC Assets Research Team, Performance Analytics · Published 19 May 2026 · Updated 15 June 2026

Information Ratio — The Information Ratio measures the consistency of excess returns relative to a benchmark. It is the active return divided by tracking error, and the benchmark-relative analog of the Sharpe ratio for active managers.

Definition

The Information Ratio (IR) measures benchmark-relative excess return per unit of tracking error. The formula is straightforward: IR = (Portfolio return - Benchmark return) / Standard deviation of (Portfolio return - Benchmark return).

The numerator is "active return" - the portion of portfolio return attributable to deviations from the benchmark. The denominator is "tracking error" - the volatility of those deviations. Together they answer: how consistently does this manager produce excess return relative to its benchmark?

IR was developed by Richard Grinold in 1989 specifically for evaluating benchmark-relative active management. Unlike the Sharpe ratio (which compares total return to total volatility), IR compares benchmark-relative return to benchmark-relative volatility. It is the appropriate metric when the relevant comparison is "did this manager add value over and above what its benchmark delivered" rather than "what was the absolute risk-adjusted return".

Interpreting Information Ratio

The thresholds depend on the benchmark and tracking error. A market-neutral hedge fund with 5% tracking error and 4% active return has IR of 0.8 (excellent for that strategy). A large-cap mutual fund with 1% tracking error and 0.7% active return has IR of 0.7 (excellent for that constraint).

The Fundamental Law of Active Management

[!key] Grinold's Fundamental Law of Active Management decomposes IR into two components: IR ≈ IC × √Breadth. Information Coefficient (IC) is the correlation between the manager's forecasts and subsequent outcomes - pure skill. Breadth is the number of independent investment decisions made per year. The decomposition explains a structural feature of investment management: systematic strategies with many decisions (e.g., quantitative equity with thousands of position decisions annually) can achieve higher IR than concentrated discretionary strategies with few decisions, even if the individual skill (IC) is lower for the systematic approach.

A discretionary stock-picker with IC of 0.10 and 30 independent decisions per year achieves IR of 0.10 × √30 ≈ 0.55. A quantitative manager with IC of only 0.04 but 1,000 independent decisions per year achieves IR of 0.04 × √1,000 ≈ 1.26. The systematic manager's lower per-decision skill is more than compensated by the breadth of decisions.

This framework explains why systematic strategies have proliferated in active management. Decision breadth is a multiplier on whatever skill exists; for managers with modest skill but operational ability to deploy many independent decisions, the math favours systematic approaches.

IR vs Sharpe Ratio

For a fundamental long-short hedge fund without specific benchmark, Sharpe is the standard metric. For a large-cap equity mutual fund benchmarked against the S&P 500, IR is more meaningful. Many sophisticated allocators look at both.

Common Misconceptions

"Higher IR is always better." Within a strategy and benchmark, yes. Across strategies with different benchmarks, no. A 0.7 IR market-neutral strategy may produce a different absolute return than a 0.7 IR active equity strategy. IR is comparable within categories, less comparable across them.

"IR captures all of skill." Specifically, it captures skill within the manager's benchmark-relative tracking-error budget. A manager who happens to have factor exposures that match the benchmark's factor profile may have an artificially low IR despite genuine skill in less-modelled dimensions.

"Tracking error should always be minimised." False. Lower tracking error means closer to benchmark, which (for active management) means less active value-add. The relevant question is whether tracking error is being used productively (high IR) or unproductively (low IR). A 1% tracking error producing 0.5% active return is more valuable than 5% tracking error producing 1% active return.

Applying the Fundamental Law

Consider two managers with apparently similar IR of 0.8:

Both deliver IR 0.8 but through very different mechanisms. The discretionary manager requires high per-decision skill to compensate for limited breadth. The quantitative manager requires only modest per-decision skill, compensated by large breadth.

The institutional implications:

• High-IC strategies are vulnerable to skill loss (key person, regime shift, edge erosion)
• High-breadth strategies are vulnerable to capacity limits (alpha decays as AUM grows)
• The right manager depends on which characteristic the institution values

The Persistence Question

Information Ratio persistence is empirically weak. A meta-analysis of active equity managers shows:

• Top-quartile IR managers have ~30-35% probability of remaining top-quartile next year (vs 25% if random)
• Top-decile IR managers have ~15-20% probability of remaining top-decile (vs 10% if random)
• 5-year persistence is meaningful but small; 10-year persistence approaches random

The implication: past IR is informative about future IR but only modestly. Mechanical selection of past winners produces only modest improvement over random selection. Sophisticated manager research combines historical IR with process due diligence and forward-looking assessment of competitive position.

References

1. Bodie, Z., Kane, A., & Marcus, A. J. (2021). Investments (12th ed.). McGraw-Hill.
2. Sharpe, W. F. (1994). The Sharpe Ratio. Journal of Portfolio Management, 21(1).
3. CFA Institute. Portfolio Management: Performance Evaluation. CFA Program Curriculum.