That’s a huge amount of data that can’t be retrieved in a single API call. You’ll need to do the following for each ticker:
the expiration is easy to compute. It’s the third Friday of each month. For the strike price, it’s vary depending on the market price of the underlying. For lower priced stocks (usually $25 or less), intervals are at 2.5 points. Higher priced stocks have strike price intervals of 5 point (or 10 points for very expensive stocks priced at $200 or more). Index options typically have strike price intervals of 5 or 10 points. So for each third Friday of each month, you can build a array of strikes with a predefined interval, e.g, [50, 55, 60, …]. With these parameters, you can loop through the API and get the data.
So programatically (python), you would something like:
for date in [3rdFriday1, 3rdFriday2, 3rdFriday3, …]:
for exp in range(50, 300, 2.5): # step of 2.5, 5 or 10 etc
historicalprice(exp, date)
We can help you if you want.
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Can I receive 15 min time series using it?
That’s a huge amount of data that can’t be retrieved in a single API call. You’ll need to do the following for each ticker:
the expiration is easy to compute. It’s the third Friday of each month. For the strike price, it’s vary depending on the market price of the underlying. For lower priced stocks (usually $25 or less), intervals are at 2.5 points. Higher priced stocks have strike price intervals of 5 point (or 10 points for very expensive stocks priced at $200 or more). Index options typically have strike price intervals of 5 or 10 points. So for each third Friday of each month, you can build a array of strikes with a predefined interval, e.g, [50, 55, 60, …]. With these parameters, you can loop through the API and get the data.
So programatically (python), you would something like:
for date in [3rdFriday1, 3rdFriday2, 3rdFriday3, …]:
for exp in range(50, 300, 2.5): # step of 2.5, 5 or 10 etc
historicalprice(exp, date)
We can help you if you want.