BUG or DOC: pd.read_csv with parse_dates does not recognize timezone
When parsing a timezone-aware datetime in a csv file with  `pd.read_csv` + `parse_dates`, it returns naive timestampes converted to UTC, and it was a surprise for me.

#### Example

Consider we are reading the following data. Let's say its name is `pandas_read_csv_bug.csv`.
It is a simple timeseries data with timezone (UTC+09:00) specified.

```
dt,val
2018-01-04 09:01:00+09:00,23350
2018-01-04 09:02:00+09:00,23400
2018-01-04 09:03:00+09:00,23400
2018-01-04 09:04:00+09:00,23400
2018-01-04 09:05:00+09:00,23400
```

I want to read it with `pd.read_csv` using `parse_dates` keyword argument activated.
If working properly, this seems to be the most elegant solution.

```python
import pandas as pd
df = pd.read_csv('pandas_read_csv_bug.csv', parse_dates=['dt'])
```

However, the result is a data frame `df` with strange timestamps.


  | dt | val
-- | -- | --
0| 2018-01-04 00:01:00 | 23350
1| 2018-01-04 00:02:00 | 23400
2| 2018-01-04 00:03:00 | 23400
3| 2018-01-04 00:04:00 | 23400
4| 2018-01-04 00:05:00 | 23400

#### Problem description

My surprise was,

1. The parsed datetimes are timezone-naive. `df['dt'].iloc[0].tz is None == True`
2. The timestampe is automatically converted to UTC.

My first impression was that it shouldn't be the best possible behavior.
However, as an UTC offset does not uniquely corresponds to a single timezone, this could be the safest/most reasonable behavior. 
In that case, the documentation should mention this behavior.


#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-29-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 3.3.1
pip: 9.0.3
setuptools: 38.5.1
Cython: None
numpy: 1.15.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
