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Description
Pandas version checks
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I have checked that this issue has not already been reported. 
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I have confirmed this bug exists on the latest version of pandas. 
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I have confirmed this bug exists on the main branch of pandas. 
Reproducible Example
import pandas as pd
data =[-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,-2,7729964027,7729965641,7729965103,7729966179,7729968330,7729969406,7729971020,7729969406,7729969944,7729969406,7729969406,7729969944,7729971558,7729972633,7729973171,7729973171,7729973171,7729969406]
df=pd.DataFrame(data,columns = ['data'])
df.data.rolling(10).skew()
43   -1.778781e+00
44   -3.162278e+00
45   -1.311680e+03
46    2.681674e+04
47    5.244346e+03
48    5.565501e+03
49    4.143785e+04
50    1.921654e+04
51   -7.723187e+03
52    1.171920e+04
53    1.171920e+04
df.data.tail(10).skew()
0.16889762763904356
#Same problem for kurt()!
df.data.rolling(10).kurt()[-1:]
53   -4.518855e+10
df.data.tail(10).kurt()
-2.198110595961745Issue Description
When there is a large spread in the exponent of values in the data, then rolling().skew() and tail().skew() come to different results.
Expected Behavior
The results must be equal.
Installed Versions
INSTALLED VERSIONS
commit           : 06d2301
python           : 3.9.7.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19044
machine          : AMD64
processor        : AMD64 Family 23 Model 1 Stepping 1, AuthenticAMD
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : Russian_Russia.1251
pandas           : 1.4.1
numpy            : 1.22.2
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 22.0.4
setuptools       : 62.4.0
Cython           : 0.29.27
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.7.1
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.3
IPython          : 8.0.1
pandas_datareader: None
bs4              : 4.10.0
bottleneck       : None
fastparquet      : None
fsspec           : None
gcsfs            : None
matplotlib       : 3.5.1
numba            : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyreadstat       : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.3
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
zstandard        : None