Information Ratio: Is Your Fund Manager Actually Beating the Benchmark?

Every active fund in India sells you the same promise: give us a fee, and we’ll do better than the index. The information ratio is the number that checks whether that promise was kept with any consistency. It takes the extra return a fund earned over its benchmark and divides it by how wobbly that extra return was. A manager who beats the index by a small margin every single year scores better than one who swings between big wins and big misses, even if the second one has a higher average.

That sounds like a small distinction. It isn’t. Plenty of funds look brilliant over one lucky stretch, and the information ratio is one of the simplest tools for telling skill apart from a good run. Below we explain the formula in plain terms, work through a full example with two made-up funds, and then go over the traps that catch people when they read this number on a factsheet.

What the information ratio actually measures

Wikipedia’s entry on the information ratio defines it as the active return of a portfolio (its return minus the benchmark’s return) divided by the tracking error, which is the standard deviation of that active return. In other words, it tells you how much additional return you got for each unit of additional risk the manager took relative to the index.

Two terms carry the whole idea, so let’s pin them down.

• Active return is simply the gap between the fund and its benchmark for a period. If the fund made 14% in a year and its benchmark made 12%, the active return for that year is 2 percentage points.
• Tracking error, in this formula, is the standard deviation of those yearly (or monthly) gaps. It measures how consistent the outperformance was, not how volatile the fund itself was.

The formula is short:

Information ratio = (Portfolio return − Benchmark return) ÷ Tracking error

Where the numerator is usually the average active return across the periods you’re studying, and the denominator is the standard deviation of the same series. A higher number means the manager delivered more excess return per unit of deviation from the index.

Why the denominator matters so much

Most investors look only at the numerator. “This fund beat the Nifty by 3% a year” is an easy line to sell. What it hides is the path.

Investopedia’s explainer on the information ratio makes this point with a neat contrast. A fund that beats its benchmark by 2% every month would have a very low tracking error in the IR calculation, even though it isn’t trying to copy the index. Another fund that beats the benchmark by 10% one month and lags by 6% the next would have a much higher tracking error, even if its average outperformance came out the same.

Investopedia also flags a confusion worth clearing up. For passive index funds, “tracking error” usually means how closely the fund follows its index, and smaller is better because the fund is meant to copy. Inside the IR formula, the same phrase is about the consistency of an active fund’s excess returns. Same words, different job.

A fund that beats the index by a little, every year, is telling you something about skill. A fund that beats it by a lot, some years, may just be telling you about luck.

Information ratio vs the Sharpe ratio

If you’ve read our guide to the Sharpe ratio, the structure will look familiar. Both are a return figure divided by a risk figure. The difference is the yardstick.

• The Sharpe ratio measures return above a risk-free rate, divided by the total volatility of the fund.
• The information ratio measures return above a risky benchmark index, divided by the volatility of that gap.

Wikipedia puts the practical split nicely: Sharpe is useful for attributing a portfolio’s absolute returns, and the information ratio is useful for attributing its relative returns. So if your question is “was this fund worth owning at all compared with a safe deposit?”, Sharpe is the better lens. If your question is “did this manager earn the fee compared with just buying the index fund?”, the information ratio is the sharper tool. For lopsided, downside-heavy return patterns, the Sortino ratio adds a third angle by counting only the bad months.

A worked example with two funds

Let’s build this from scratch. The numbers below are entirely hypothetical, made up for illustration. They don’t describe any real fund or index.

Imagine a large-cap benchmark that returned the following over six years: 12%, −3%, 25%, 5%, 18% and 8%. Two active funds track it.

Fund A (call it the steady one) returned 14%, −1.5%, 24.5%, 7.5%, 19% and 9.5%.

Fund B (the exciting one) returned 21%, −9%, 37%, 1%, 25% and 6%.

Step 1: Work out the active return each year

Subtract the benchmark from each fund, year by year.

• Fund A: +2.0, +1.5, −0.5, +2.5, +1.0, +1.5 percentage points.
• Fund B: +9, −6, +12, −4, +7, −2 percentage points.

Already you can see the personalities. Fund A lagged in only one year, and by just half a point. Fund B lost to the index in three of the six years, sometimes badly.

Step 2: Average the active returns

• Fund A: (2.0 + 1.5 − 0.5 + 2.5 + 1.0 + 1.5) ÷ 6 = 8 ÷ 6 = about 1.33 points a year.
• Fund B: (9 − 6 + 12 − 4 + 7 − 2) ÷ 6 = 16 ÷ 6 = about 2.67 points a year.

On the headline number, Fund B wins comfortably. It beat the benchmark by twice as much on average. This is the figure most marketing material leads with.

Step 3: Calculate the tracking error

Now take the standard deviation of each set of active returns. We’ll use the sample standard deviation, which divides the sum of squared deviations by the number of years minus one, the same thing Excel’s STDEV function does.

For Fund A, the squared gaps from the 1.33 average add up to about 5.33. Divide by 5 and you get a variance of about 1.07. The square root of that is a tracking error of roughly 1.03 points.

For Fund B, the squared gaps from the 2.67 average add up to about 287.3. Divide by 5 for a variance of about 57.5, and the square root gives a tracking error of roughly 7.58 points.

Step 4: Divide

• Fund A: 1.33 ÷ 1.03 = an information ratio of about 1.29.
• Fund B: 2.67 ÷ 7.58 = an information ratio of about 0.35.

The picture flips. Fund A earned less extra return, but it earned it so reliably that each point of deviation from the index was paid back far better. Fund B’s bigger average came with so much noise that you’d struggle to tell skill from coin-flipping across just six years.

Here’s the part we find most useful in practice. Suppose you had joined Fund B at the start of year two. You’d have trailed the index by 6 points straight away, and plenty of real investors redeem after a year like that. The information ratio quietly captures that experience. Fund A never put you through it.

A big average outperformance with a big tracking error often means the investor who actually stayed for the good years was rare.

What counts as a good information ratio?

There’s no official cut-off, but two reference points come up often. Investopedia says that a higher IR, generally above 0.5, suggests an actively managed fund is consistently outperforming its benchmark. Wikipedia, citing Grinold and Kahn’s book Active Portfolio Management, notes that top-quartile investment managers typically achieve annualised information ratios of about one-half.

Put those together and the message is sobering. An information ratio around 0.5 is already good company. Numbers well above 1 over long periods are rare, so if you see one, check the period and the benchmark before getting excited. Our Fund A’s 1.29 is the kind of figure that happens in a made-up example; in the real world it would deserve a close look.

Investopedia also recommends judging the IR over periods of at least three years, and notes that publications often report it over one-, three- and five-year windows. Longer windows generally give a more reliable read on a manager’s skill. A one-year IR is closer to a weather report than a climate record.

Where the information ratio misleads

It’s a good number. It isn’t a complete one. A few things to watch:

The benchmark choice can flatter the fund

Everything is measured relative to the index. Pick an easy benchmark and almost any fund looks like a star. A mid-cap-heavy fund compared with a pure large-cap index might show strong “active return” that is really just mid-caps having a good run. Always ask whether the benchmark matches what the fund actually holds.

Short windows are noisy

With only a few data points, the standard deviation itself is unreliable. One unusually calm stretch can shrink tracking error and inflate the ratio. That’s why monthly data over several years beats annual data over three.

Annualising is an approximation

The ratio is often annualised. Wikipedia points out that the common practice of taking the difference between the annualised portfolio return and the annualised benchmark return is an approximation, because annualising a difference isn’t the same as differencing annualised terms. The practical lesson: when you compare two funds, make sure both IRs were calculated the same way, on the same frequency of data.

It ignores leverage and uses arithmetic returns

Wikipedia lists the main criticism as the ratio’s use of arithmetic rather than geometric returns, and the fact that it ignores leverage. In some cases this can make the ratio negative even when a manager has added value over the benchmark, or the other way round. For most plain equity mutual funds this is a minor issue, but for leveraged or hedge-fund style strategies it matters more.

There’s more than one version

Some analysts use Jensen’s alpha in the numerator and a regression-adjusted tracking error in the denominator. Wikipedia notes this version is often called the appraisal ratio, to tell it apart from the common definition. If two sources give wildly different IRs for the same fund, a different method is the usual reason.

How to use it when picking a fund

We’d keep it simple. When you’re comparing active funds in the same category, look at the information ratio over three and five years, not one. Favour funds whose IR stays reasonably positive across different windows rather than one that spikes in a single period. Then put it next to the expense ratio. If an active fund’s information ratio is weak and its fees are high, a low-cost index fund on the same benchmark is the honest alternative.

You can also use it on your own portfolio. If you pick stocks yourself, line up your yearly or monthly returns against the Nifty 50 or whichever index fits your style, and run the four steps above in a spreadsheet. A low or negative number is useful feedback. Often the fix isn’t more stock tips, it’s tighter position sizes and clearer exit rules, the ground our risk management in trading guide covers.

Quick recap

The information ratio is the average return a portfolio earned above its benchmark divided by the standard deviation of that excess, the tracking error. It rewards consistent outperformance over flashy, erratic outperformance. Around 0.5 is generally considered good. Use it over several years, check that the benchmark is fair, and make sure any two ratios you compare were worked out the same way.

Disclaimer: This article is for educational purposes only and is not investment advice. The examples use hypothetical numbers. Investing and trading involve risk; please do your own research or consult a SEBI-registered adviser before making investment decisions.