Obviously, each stock should possess just one volatility. However, when estimating implied volatility, different strike prices might offer us different implied volatilities. More specifically, the implied volatility based on out-of-the-money options, at-the-money options, and in-the-money options might be quite different. Volatility smile is the shape going down then up with the exercise prices, while the volatility skewness is downward or upward sloping. The key is that investors' sentiments and the supply and demand relationship have a fundamental impact on the volatility skewness. Thus, such a smile or skewness provides information on whether investors such as fund managers prefer to write calls or puts, as shown in the following code:

from pandas.io.data import Options
from matplotlib.finance import quotes_historical_yahoo
# Step 1: define two functions 
def call_data(tickrr,exp_date):
    x = Options(ticker,'yahoo')
    data= x.get_call_data(expiry=exp_date...