Retrieving option data from Yahoo! Finance

In the previous chapter, we discussed in detail how to estimate implied volatility with a hypothetic set of input values. To use real-world data to estimate implied volatility, we could define a function with three input variables: ticker, month, and year as follows:

def get_option_data(tickrr,exp_date):
    x = Options(ticker,'yahoo')
    puts,calls = x.get_options_data(expiry=exp_date)
    return puts, calls

To call the function, we enter three values, such as IBM, 2, and 2014, when we plan to retrieve options expired in February, 2014. The code with these three values is shown as follows:

def from pandas.io.data import Options
import datetime
ticker='IBM'
exp_date=datetime.date(2014,2,28)
puts, calls =get_option_data(ticker,exp_date)
print puts.head()
Strike              Symbol  Last  Chg   Bid   Ask  Vol  Open Int
0     100  IBM140222P00100000  0.01    0   NaN  0.03   16        16
1     105  IBM140222P00105000  0.04    0   NaN  0.03   10   ...