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Some of the issues with this sort of request is: a) Today's S&P 500 components are not the same from 1 Jul 2013. By using today's components you are introducing pre-inclusion/survivorship bias. Are you going to be able to find data on the delisted stocks? eg. Since 1 Jul 2013, Sprint Corporation, BMC Software, NYSE Euronext, Molex, Life Technologies, ...


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I faced the same issue some years ago and I solved by implementing the R script reported here; now, with new Yahoo disclaimer rules, it seems to be broken, but, anyway you should be able to replicate the data mining process using that script together with this. If you're pretty confident with R, you should be able to do that. Alternatively, you can visit ...


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Hope you will not mind if I place myself in continuous time. The discounted stock price at $T$ is $e^{-rT}S_T$. As you know that it is a martingale, you have that $\mathbf{E}^{\mathbf{P}}[e^{-rT}S_T | \mathscr{F}_t] = e^{-rt} S_t$ when $t\leq T$ which you can rewrite as $\mathbf{E}^{\mathbf{P}}\left[\frac{e^{-rT}S_T}{e^{-rt} S_t} | \mathscr{F}_t\right] = 1$ ...


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You could compare a Greenshoe option to overbooking a plane: airlines tend to sell more tickets than there are seats in the plane in the expectation that some people will not show up. If they do not oversell then the plane will take off partially empty, which makes it more expensive. But if they oversell too much, then there will be many angry passengers ...


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Maybe a Social Trading platform would be what you're looking for? They allow you to put together a portfolio for the world to view. Some even make it tradeable, usually as ETF (which carries the usual fees for investors, which are then split between you and the provider).


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In addition to the above answers - You should be very careful that you do not introduce survivorship bias in your creation of indices and choose your data source carefully to remove such bias. For example, Yahoo Finance only contains currently-listed securities.


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Both R and Python can do this very nicely. For Python you would need the pandas package and its dependencies. pandas has a lot of basic statistics, but for more advanced statistics like it looks like you want to do, you can use the statsmodels package, which can work directly with pandas data types. It can also download the csv files directly off the ...


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It is essentially a statistical exercise, so I would choose R.



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