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    $\begingroup$ This is a great answer and a real tour-de-force of the functionality of Dataset. $\endgroup$ Commented Sep 13, 2018 at 8:52
  • $\begingroup$ That said, it's probably a little more complicated and duplicative than would be required in a typical finance application. There may well be applications where it makes sense to store everything in the form of time series, but that is a space/memory intensive approach. In most cases, I imagine, a researcher would want time series as the exception, rather than the rule and could create them "on-the-fly" as required rather than storing them for every stock. $\endgroup$ Commented Sep 13, 2018 at 8:56
  • $\begingroup$ Still, Edmund's answer is a superb illustration of how a hierarchical database should be set up: 10/10! $\endgroup$ Commented Sep 13, 2018 at 8:57
  • $\begingroup$ @JonathanKinlay The duplicity is for the sake of introducing the idea. In practice you would not need so many Dataset objects as you can store the additional elements in the original object. $\endgroup$ Commented Sep 14, 2018 at 11:05
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    $\begingroup$ @JonathanKinlay Also, do not discount the utility of TimeSeries objects. There is framework supporting these objects for time series analysis ( reference.wolfram.com/language/guide/TimeSeries.html ), which is quite useful for financial analysis applications. $\endgroup$ Commented Sep 14, 2018 at 11:12