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The sample range could be used as an index of dispersion. However, there are objections. One is that this statistic is obviously sensitive to outliers. Another is that for many population distributions there are measures with much better characteristics, even ignoring the problem of outliers.
This would obviously depend on the popularity of the stock in question. Most of the stocks are in the hundred thousands, if not millions of shares on a daily basis.
Indexing can be faster than sorting. It can also be slower. It depends on how many rows your predicate clause is selecting, and on the data dispersion represented by those index keys. If you are selecting a few rows, such as less than 4% of the table, then by all means use an index. If you are selecting a lot of rows, such as more than 25% of the table, then the use of the index will usually degrade performance, so go for the full table scan followed by a sort. (Of course, now you are adding the use of sort space, so that is a consideration.) The break-even point depends on the particular RDBMS and on the structure of the data. If your RDBMS supports EXPLAIN PLAN, then use it, and learn to know what it means. Also, make sure you understand your data, because (sometimes) only you know the best way to query it, and it might make sense to override the optimzer and force a certain execution plan based on your knowledge.
There are many advantages of performing a database normalization. Some of the advantages include faster index searching, data commands are faster with less indexes and a more compact database with less null data.