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Money.net provide a relative to Bloomberg Terminal solution. The platform is a web-application, so you don't need to download the desktop client itself. You could also download tick-data in trial 14 period. But I am not sure about limitations. Their product is subscription based, and it's commercial, but I guess they could extend your trial period for ...


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You could ignore the problem, throw away returns for the first minute in each trading session, or you could keep those first-minute returns in a second dataset and analyze that to estimate the overnight gap volatility. Also, since you are an academic and using minute bars, I'm sure you are aware of the issues with bid-ask bounce and volatility estimation for ...


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https://algoseek.com/ is an option if you are looking for historical intraday stock data in the US market. You can easily download their samples and the dataset you need on their Explore Data page.


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Last time I checked, algoseek has that kind of data. Their S&P 500 Trades and Quotes+minute bar data set contains OHLC, FINRA volume and etc. You can find a sample of their dataset here


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It depends. For example, if you're doing option pricing in the log normal world returns are completely described by the mean and standard deviation. If you add jumps, you would also need to parametrize the underlying Poisson process which is fully described by one parameter and the jump size. In other words, if you have a (log)normal distribution and the ...


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All index data is available here: https://www.msci.com/end-of-day-data-search However, I don't believe the daily data extends to 1991 for this specific index.


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It is hard to tell, because means and standard deviations are hard to estimate. Take a look at the example below from De Miguel et al: The row you are interested in is the third row ($mv$). They simulate normally distributed data, and realise that only when you have 6000 months of data (i.e. 500 years), mean variance starts to be close to the true sharpe ...


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First of all, welcome. I don't think there's a golden rule for that. Trial and Error and see what works best for your use-case. Personally, I think there might be an argument for a 12 month window, since it follows the momentum logic in it's orginal formulation. And a longer horizon might be more stable.


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