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As barrycarter stated in the comment - the value of a set of [European!] options is the sum of the values of the individual options. This is simply follows from integral of a sum being a sum of integrals. butterfly\,option\,price = \\ \int_0^\infty butterfly\,payoff(S) dS = \\ \int_0^\infty (call\,payoff(S,K)+call\,payoff(S,K')+call\,payoff(S,K'')) dS ...

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There was a recent thread discussing this historic options data That data source mentioned there is commercial, though reasonably priced. Their data in CSV format readily ingestible by Excel. One note of caution is options' daily closing quotes are not always accurate.

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From e.g. the CBOE web site you are able to download a full table of option quotes (delayed) for a specific stock (menu quotes - delayed quotes). Take it from there, appply data manipulation (Excel VBA, R, Python..) to the extent needed and then you should be be able to end up with the desired result. This wouldn't be a simple copy & paste procedure; ...

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You can guesstimate by vega weighted implied vol. This is why: Say that you have a portfolio of options with prices $P_j$. Each one of them has a different pricing function $f_j$ (as function of vol) and a different implied vol $\sigma_j$. For each option $f_j(\sigma_j)=P_j$. Now you put them together in a single product. If the implied vol of the product ...

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