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Although I think your question will be flagged for "basic knowledge" you can find free sources for this data including Yahoo Finance, Quandl. Commercial data vendors also provide this information. However, you really need to define what sort of data you are trying to find. Spot prices (for physical delivery), spot prices (for cash settled) or futures data ...


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Bloomberg or datastream are the only possible sources.


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This data isn't free obviously, but Euronext (the index provider) might be inclined to give you this information if it's for academic purposes. It's advertised on their website here: https://www.euronext.com/fr/market-data/products/end-day-index-data


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As you said yourself, Yahoo finance provides the historical stock data. The only thing left is to know the historical composition of the CAC40. This information can be extracted from the french wikipedia site about the CAC40, or from the source @jean-paul-sartre mentioned. In my answer I will concentrate on how to scrap the information. Some time ago I ...


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You can try Quandl. They have a nice API to R and Python which you can use to do the data-wrangling.


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I'm not sure if you are looking for the components only or if you want more data, like the weights in the index. Unfortunately, unlike most other data on the web, it's hard to get any good financial data for free. The only easy way is to pay for accessing it through a financial data provider such as Bloomberg (with MEMB function when you select an index). ...


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No, it's not correct. The 1000 you invest at the beginning of the second year should also be discounted, That 1000 also has a present value. This gives: $$NPV = \frac{2200}{(1+R)^2} - \frac{1000}{(1+R)} - 1000$$ with $R$ the annual rate. Remember, you cannot simply add incoming or outgoing cash flows that occur at different times.


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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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There are two answers to your question If you want to use the Neston-Nandi model, you can use it directly with the parameters that you already show above: model = list(omega = 0.000001, alpha = 0.5, beta = 0.4) In r, the fOptions package has an HN model that can use them: HNGOption(TypeFlag, model, S, X, Time.inDays, r.daily) If you want to calculate ...



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