read_sql_query parse_dates regression from 0.18.0 to 0.18.1
Based on a sqlite database [my_database.zip](https://github.com/pydata/pandas/files/314395/my_database.zip) created from the file [source.zip](https://github.com/pydata/pandas/files/314358/source.zip) in a table `my_table`. I get different results when parsing the dates in the method `read_sql_query` between version 0.18.0 and 0.18.1.

The date format looks like this:  `"2015-05-01 00:00:00.000000"`
#### Code Sample, a copy-pastable example if possible

```
import pandas as pd
from sqlalchemy import create_engine
engine = create_engine('sqlite:///my_database.db')
result = pd.read_sql_query('SELECT * from my_table;', engine, parse_dates={"RDD": 'D'})
```
#### Expected Output (0.18.0)

| RDD | QTY |
| --- | --- |
| 2015-05-01 | 1.0 |
| 2015-05-04 | 1.0 |
| 2013-12-03 | 1.0 |
| 2011-09-02 | 1.0 |
| 2010-09-01 | 20.0 |
#### Current Output (0.18.1)

| RDD | QTY |
| --- | --- |
| 2115-12-30 20:53:38.800017408 | 1.0 |
| 2115-12-30 20:53:38.800017408 | 1.0 |
| 2115-12-30 20:53:38.800017408 | 1.0 |
| 2115-12-30 20:53:38.800017408 | 1.0 |
| 2116-08-08 09:38:37.216342016 | 20.0 |
#### output of `pd.show_versions()`

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.11.0
scipy: 0.17.0
statsmodels: None
xarray: None
IPython: 4.1.2
sphinx: None
patsy: None
dateutil: 2.5.2
pytz: 2016.3
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.1
openpyxl: None
xlrd: 0.9.4
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None
