Handling a CustomBusinessDay in time-based .rolling()
Starting with 10 business days following Christmas Eve:

```
from pandas.tseries.offsets import CustomBusinessDay
from pandas.tseries.holiday import USFederalHolidayCalendar

days = CustomBusinessDay(calendar=USFederalHolidayCalendar())

df = pd.DataFrame({'value': np.arange(n)},
                  index=pd.date_range('2015-12-24', periods=n, freq=days))
```

I can compute the three-day sum of the values with just:

```
In [21]: df.rolling('3d').sum()
Out[21]:
            value
2015-12-24    0.0
2015-12-28    1.0
2015-12-29    3.0
2015-12-30    6.0
2015-12-31    9.0
2016-01-04    5.0
2016-01-05   11.0
2016-01-06   18.0
2016-01-07   21.0
2016-01-08   24.0
```

But this is purely in terms of _Gregorian_ calendar days, not the _business_ calendar days that I had created the DataFrame with.

I can easily compute

```
df.index - 3*days
```

though I get a performance warning:

> Non-vectorized DateOffset being applied to Series or DatetimeIndex

But I can't just pass this offset directly:

```
In [23]: df.rolling(3*days).sum()
...
ValueError: <3 * CustomBusinessDays> is a non-fixed frequency
```

I would like to be able to handle a `CustomBusinessDay` in `.rolling()`. (Because the DataFrame may come from any source, it would be easier to just pass the `DateOffset` object to `.rolling()` instead of using anything specific to the DataFrame's index.)

I know that the `freq` parameter was deprecated in 0.18, though 0.19 kinda brings this back in `window`. Is there an intrinsic reason `window` can't handle a `CustomBusinessDay`?
