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The answer to your question probably depends on the type of the security you want to query the data from, their vendor (not Bloomberg, the original vendor) and your license with Bloomberg. I don't remember having no access to intraday data, but I remember having limited history for sure (more data implied more fees as far as I can remember). But in ...

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There is a vast literature on modelling time-series with periodcities. Rob Hyndman is one of the leading reseaerchers in this area. He has published the R package forecast and a free online text book on this subject (with another package and R code in the book). Your task is covered starting here.

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In my case, it really depends if you are using any software at all. I usually get my Discount Factors with a 15 decimals precision. So im always storing at least 15 digits for DF, and yields up to 7-8 as rhaskett said. For equities, i guess it's pretty much the same as for yields, or even less. Nevertheless i store any return, price or ratio with a 7-8 ...

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As background, Floating point precision is a way of storing numbers such that the precision is relative to the largest digit. For instance, the number $0.00123$ stored in fixed precision needs 6 digits of precision (3 zeros and the 3 non-zero numbers). However, this same number stored as floating point precision $1.23 \cdot 10^{-3}$ needs only 3 ...

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Yahoo Finance might be the best source, you have a lot of information available, Date Open High Low close Volume Adj Close*. https://uk.finance.yahoo.com/q/hp?s=VOD.L

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All option pricing formulas except this one and this one use some sort of historical volatility . I can't see how you can use the Black Sholes framework and not use some sort of historical volatility uses an order book uses geometric shapes and volume

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If you want to estimate volatility from historical data, the only best linear unbiased estimator (BLUE) is $$\sigma=\sqrt{\frac{1}{T-1}\sum_{i=1}^T (r_i-E(r_i))^2}$$ Any other estimator will hence either be biased or not consistent. Another approach could be to estimate volatility via a GARCH model, which has shown good empirical results in the past. It is ...

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