Although originally called the "appraisal ratio"
by Treynor and Black, the information ratio is the ratio of relative
return to relative risk (known as "tracking error").
Whereas the Sharpe ratio looks at returns relative to a riskless
asset, the information ratio is based on returns relative to a risky
benchmark which is known colloquially as a "bogey."
Given an asset or portfolio of assets with random returns designated
by `Asset`

and a benchmark with random returns designated
by `Benchmark`

, the information ratio has the form:

```
Mean(Asset − Benchmark) / Sigma (Asset −
Benchmark)
```

Here `Mean(Asset − Benchmark)`

is the
mean of `Asset`

minus `Benchmark`

returns,
and `Sigma(Asset - Benchmark)`

is the standard deviation
of `Asset`

minus `Benchmark`

returns.
A higher information ratio is considered better than a lower information
ratio. For more information, see `inforatio`

.

To calculate the information ratio using the example data, the mean return of the market series is used as the return of the benchmark. Thus, given asset return data and the riskless asset return, compute the information ratio with

```
load FundMarketCash
Returns = tick2ret(TestData);
Benchmark = Returns(:,2);
InfoRatio = inforatio(Returns, Benchmark)
```

which gives the following result:

InfoRatio = 0.0432 NaN -0.0315

Since the market series has no risk relative to itself, the
information ratio for the second series is undefined (which is represented
as `NaN`

in MATLAB^{®} software). Its standard deviation
of relative returns in the denominator is 0.

`elpm`

| `emaxdrawdown`

| `inforatio`

| `lpm`

| `maxdrawdown`

| `portalpha`

| `ret2tick`

| `sharpe`

| `tick2ret`

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