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Information Ratio

Active Management Performance Measure Portfolio Analysis

The information ratio measures how consistently a portfolio outperforms its benchmark. It divides the portfolio's active return (the difference between the portfolio's return and the benchmark's return) by the tracking error (the volatility of that difference), producing a single number that captures both the size and the reliability of the outperformance.

Where the Sharpe ratio compares a portfolio to a risk-free asset like Treasury bills, the information ratio compares it to a specific market benchmark such as the S&P 500 or the Russell 2000. This makes the information ratio especially useful for evaluating active fund managers, whose goal is to beat a stated benchmark rather than simply earn a positive return.

Definition

The information ratio is calculated by taking the average active return of a portfolio over a given period and dividing it by the tracking error. Active return is the portfolio's return minus the benchmark's return. Tracking error is the standard deviation (a measure of how spread out a set of numbers is from its average) of those active returns over time.

Formula

Information Ratio = (Portfolio Return − Benchmark Return) ÷ Tracking Error

The numerator is the "active return," the extra return earned above the benchmark. The denominator is the tracking error, which reflects how much the active return varies from period to period. A high information ratio means the manager consistently adds value relative to the benchmark, not just occasionally.

For example, if a portfolio returns 12% annually, the benchmark returns 10%, and the tracking error is 4%, the information ratio is (12% − 10%) ÷ 4% = 0.50. That means the portfolio earns half a percentage point of active return for every percentage point of tracking error.

How to Interpret the Information Ratio

Like the Sharpe ratio, the information ratio has no universal "good" or "bad" cutoff. Its value depends on the asset class, the benchmark chosen, and the length of the measurement period. However, practitioners commonly use the following ranges as general guidelines.

Information Ratio	General Interpretation
Below 0	The portfolio underperformed the benchmark on average
0.0 to 0.25	Minimal active skill; outperformance is small or inconsistent
0.25 to 0.50	Moderate skill; consistent enough to be meaningful over time
0.50 to 0.75	Strong active management; above the median for professional fund managers
Above 0.75	Significantly high relative to historical peer groups; sustained ratios at this level are rare and warrant scrutiny

Grinold and Kahn, authors of Active Portfolio Management, suggest that an information ratio of 0.50 is considered "good" and 1.0 is "exceptional" for active equity managers. Most active managers fall well below 0.50 over long periods. Investors often evaluate ratios consistently above 0.75 over five or more years for evidence of survivorship bias, benchmark selection issues, or whether the measurement captures all relevant risks.

Practical Example

Consider two actively managed equity funds measured against the same benchmark over a five-year period.

Metric	Fund A	Fund B
Annual portfolio return	13%	11.5%
Annual benchmark return	10%	10%
Active return	3%	1.5%
Tracking error	8%	2%
Information ratio	0.375	0.75

Fund A delivered a higher raw active return (3% vs. 1.5%), but Fund B achieved its outperformance far more consistently. Fund B's tracking error of 2% means its active returns varied little from period to period, while Fund A's 8% tracking error signals wide swings. For an investor or plan sponsor selecting managers, the information ratio reveals that Fund B's alpha (excess return beyond what the benchmark delivers) is more reliable and repeatable.

Known Limitations

Limitations to Keep in Mind

Benchmark selection matters enormously. The information ratio is only as meaningful as the benchmark it uses. Comparing a small-cap growth fund to a large-cap value index will inflate the tracking error and distort the ratio. The benchmark must reflect the manager's actual investment universe.
Assumes active returns are normally distributed. Like the Sharpe ratio, the information ratio relies on standard deviation, which treats all deviations equally. If active returns are skewed or have fat tails (extreme values occurring more often than a normal distribution predicts), the ratio may understate the true risk of active bets.
Sensitive to time period. A manager can show a strong information ratio over three years and a weak one over ten. Short windows can reflect luck or favorable market conditions rather than genuine skill. Longer measurement periods provide more reliable estimates but can obscure changes in a manager's process.
Does not distinguish between upside and downside tracking error. A manager who frequently outperforms the benchmark by varying amounts will have high tracking error, just like one who frequently underperforms. The information ratio penalizes both types of deviation equally.
Can be gamed through benchmark hugging. A manager who closely mimics the benchmark while making small active bets can produce a respectable information ratio with minimal skill. The low tracking error compresses the denominator, making even tiny active returns look efficient.

Metric	What It Measures	Key Difference from Information Ratio
Sharpe Ratio	Excess return per unit of total risk	Uses risk-free rate instead of a benchmark; measures absolute risk-adjusted return
Alpha	Excess return beyond what the benchmark delivers	Measures the magnitude of outperformance without adjusting for its consistency
Tracking Error	Volatility of active returns relative to a benchmark	Measures only the consistency of active returns, not their direction or size
Calmar Ratio	Return relative to maximum drawdown	Focuses on worst-case loss rather than benchmark-relative variability

The information ratio is most useful when the goal is to evaluate an active manager against a specific benchmark. For comparing portfolios without a benchmark context, the Sharpe ratio is more appropriate. For understanding the raw outperformance without adjusting for consistency, alpha alone may suffice.

Academic Origin

The conceptual foundation for the information ratio traces back to Jack Treynor and Fischer Black's 1973 paper "How to Use Security Analysis to Improve Portfolio Selection," published in the Journal of Business. Treynor and Black proposed a framework for combining active forecasts with a passive benchmark, and the ratio of expected active return to active risk was central to their approach.

The term "information ratio" and its formal treatment as a standalone performance metric were later developed by Richard Grinold and Ronald Kahn. Their 1999 book Active Portfolio Management established the information ratio as the core measure of active management skill. Grinold and Kahn also introduced the "Fundamental Law of Active Management," which decomposes the information ratio into two components: the information coefficient (the correlation between forecasts and outcomes, or a measure of forecasting accuracy) and breadth (the number of independent bets a manager takes per year).