BUG: DataFrame bdate_range index being changed under concat()?
It looks like `concat()` changes the bdate_range index of a DataFrame:

```
In [1]: from pandas.util.testing import assert_series_equal, assert_frame_equal

In [2]: from pandas import Series, DataFrame, concat, bdate_range

In [3]: import numpy as np

In [4]: from datetime import datetime

In [5]: df = DataFrame(np.nan, index=bdate_range(datetime(2009,1,1), periods=3), columns=['A','B'])

In [7]: df2 = concat([df, DataFrame(np.nan, index=range(2), columns=df.columns)]).slice_shift(-2)

In [8]: df
Out[8]:
             A   B
2009-01-01 NaN NaN
2009-01-02 NaN NaN
2009-01-05 NaN NaN

In [9]: df2
Out[9]:
                      A   B
2009-01-01 00:00:00 NaN NaN
2009-01-02 00:00:00 NaN NaN
2009-01-05 00:00:00 NaN NaN

In [10]: assert_frame_equal(df, df2)
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-10-ea37dae851f7> in <module>()
----> 1 assert_frame_equal(df, df2)

C:\Python34\lib\site-packages\pandas\util\testing.py in assert_frame_equal(left, right, check_dtype, check_index_type, check_column_
type, check_frame_type, check_less_precise, check_names, by_blocks, check_exact)
    625         if not by_blocks:
    626             assert_index_equal(left.columns, right.columns)
--> 627         assert_index_equal(left.index, right.index)
    628
    629     # compare by blocks

C:\Python34\lib\site-packages\pandas\util\testing.py in assert_index_equal(left, right)
    562                                                                               left,
    563                                                                               right,
--> 564                                                                               right.dtype))
    565
    566

AssertionError: [index] left [datetime64[ns] <class 'pandas.tseries.index.DatetimeIndex'>
[2009-01-01, ..., 2009-01-05]
Length: 3, Freq: B, Timezone: None], right [Index([2009-01-01 00:00:00, 2009-01-02 00:00:00, 2009-01-05 00:00:00], dtype='object') o
bject]

In [16]: concat([df, DataFrame(np.nan, index=range(2), columns=df.columns)])
Out[16]:
                      A   B
2009-01-01 00:00:00 NaN NaN
2009-01-02 00:00:00 NaN NaN
2009-01-05 00:00:00 NaN NaN
0                   NaN NaN
1                   NaN NaN
```

Curiously, `concat()` also seems to change the bdate_range index of a Series, though somehow under `slice_shift()` it gets restored to its original form (which is not the case for a DataFrame):

```
In [11]: s = Series(np.nan, index=bdate_range(datetime(2009,1,1), periods=3))

In [12]: s2 = concat([s, Series(np.nan, index=range(2))]).slice_shift(-2)

In [13]: s
Out[13]:
2009-01-01   NaN
2009-01-02   NaN
2009-01-05   NaN
Freq: B, dtype: float64

In [14]: s2
Out[14]:
2009-01-01   NaN
2009-01-02   NaN
2009-01-05   NaN
dtype: float64

In [15]: assert_series_equal(s, s2)

In [17]: concat([s, Series(np.nan, index=range(2))])
Out[17]:
2009-01-01 00:00:00   NaN
2009-01-02 00:00:00   NaN
2009-01-05 00:00:00   NaN
0                     NaN
1                     NaN
dtype: float64
```

This is using v0.14.1 on 64-bit Window Python 3.4.1.
