Take a look at the documentation for Rest and Most. FinancialData returns a TimeSeries. There are many functions available for time-series processing. For time-series correlation, take a look at this post on MSE and this one on this site.
Rest
Most
FinancialData
TimeSeries
Hi Bill The correlations between no deletion and 1 day deletion
I plotted the graphs, but Return is the % change in price from the day before, so the charts just looks like noise.
I did average the Return, which did reduce the error caused by the one day deletion.
Below is the Notebook
"Surprising" and "such a difference from such a small change" always makes me think "I've made a mistake in this somehow."
Perhaps the time stamps might be too important to discard. Is there any way you could do a ListPlot with the time stamps and another without the time stamps and see if the reason for the large change becomes obvious? If that explains things then would interpolating the {value,time} points to construct value=function[time] still make your computations easy
Excellent job Bill
I had manually removed the first element from the first list because it was the easiest. I did a correlation test between the first list and the next two lists. My method resulted in a correlation near zero for list 1 related to lists 2 & 3. The data is time stamped, I just removed the time stamp for easier computations. I then used your method that basically removes the last element in the list. I was quite surprised to find a correlation of 30% between list 1 with both lists 2 & 3. There are 168 elements in each of the three lists, it was quite surprising to find such a difference between either removing the first versus removing the last element.
Thanks so much for your help.
Perhaps
lists={{1,2,3},{4,5,6,7},{8,9}}; minlen=Min@@Map[Length,lists]; res=Map[Take[#,minlen]&,lists]
which returns
{{1,2},{4,5},{8,9}}
