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 ...