Multithreaded access to Series multiply (or division) operator causes segmentation fault
I have run across some really weird situation where I get segmentation fault only when multiple threads access the same code simultaneously (problems with re-entrancy?). Also this only occurs with certain datasets and I couldn't reproduce it with toydata.

The data.p file required can be downloaded from here:
https://copy.com/WMQ6UP1tHjdE

This is the sample code:

```
import pickle
import concurrent.futures
import pandas as pd
import numpy as np

data = pickle.load(open('data.p', 'rb'))

# cannot reproduce the bug with toy data!
# data_l = pd.Series(np.random.randn(100))
# data_l.index = pd.tseries.index.DatetimeIndex(start='1901-01-01', periods=100, freq='D')
# data_r = pd.Series(np.random.randn(1000))
# data_r.index = pd.tseries.index.DatetimeIndex(start='1900-01-01', periods=1000, freq='D')
# data_r['1900-01-01':'1900-06-30'] = np.nan


def myfun():
    return data[0]['AdjClose(GBP)'] * data[1]
    # return data_l * data_r

# if using only one thread (ThreadPoolExecutor(1)) everything works...
with concurrent.futures.ThreadPoolExecutor(25) as executor:
    futures = []
    for _ in range(100000):
        futures.append(executor.submit(myfun))
    for fut in concurrent.futures.as_completed(futures):
        if fut.exception():
            print(fut.exception())
        else:
            print("Success!")
```
