BUG:unexpected behavior of pandas 1.1.1 dt.normalize() on pre-epoch dates
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
print(pd.__version__)
1.1.1

df = pd.DataFrame({'year': [1969, 2016],'month': [1, 1],'day': [1, 1],'hour': [9, 9]})
df=pd.to_datetime(df)

df

Out[10]: 
0   1969-01-01 09:00:00
1   2016-01-01 09:00:00
dtype: datetime64[ns]

df.dt.normalize()

Out[11]: 
0   1969-01-02
1   2016-01-01
dtype: datetime64[ns]
```

#### Problem description

I would expect pre-epoch behavior to be the same as post-epoch

#### Expected Output
```
Out[10]: 
0   1969-01-01 09:00:00
1   2016-01-01 09:00:00
dtype: datetime64[ns]

df.dt.normalize()

Out[11]: 
0   1969-01-01
1   2016-01-01
dtype: datetime64[ns]
```

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

<details>
commit           : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python           : 3.6.10.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.17763
machine          : AMD64
processor        : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : None.None

pandas           : 1.1.1
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 49.6.0.post20200814
Cython           : 0.29.21
pytest           : 6.0.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.3
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.8.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : 1.3.19
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.50.1


</details>
