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I am working with four different time series which have the same first and last dates, but a different number of observations. One time series (svq) includes weekend data, the other three don't include weekend data, but seem to be missing a few days each. I can get the Intersection of "Dates" common to all four series and map each index over the common dates to get a matching set of values, but that is perhaps not the best way to get those values. Can someone suggest a better way?

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  • $\begingroup$ Perhaps you could use TimeSeriesResample[{<time series>}, "Intersection"] $\endgroup$ – user42582 May 16 '18 at 19:49
  • $\begingroup$ "doesn't perform as expected is due to poor programming or incomplete understanding of the underlying task" - I get it $\endgroup$ – George Wolfe May 16 '18 at 20:18
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    $\begingroup$ for the record, I wasn't aware you could do this with TimeSeriesResample until I read this question; that's the reason I like mma.se; it forces you to be honest with what you know and learn the rest $\endgroup$ – user42582 May 16 '18 at 20:40
  • $\begingroup$ I didn't really understand the full capabilities of the function. TimeSeriesResample[ ts , {starttime,endtime,"BusinessDay"} also worked. $\endgroup$ – George Wolfe May 17 '18 at 20:14
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Compare and contrast the following example series:

ts1 = TimeSeries[{1, 2, 3, 4}, {{1, 2, 3, 4}}]
ts1 // ListLinePlot[#, Mesh -> Full] &

Blockquote

ts2 = TimeSeries[{5, 4, 3, 2, 1}, {{1, 1.3, 2, 3.5, 4}}];
ts2 // ListLinePlot[#, Mesh -> Full] &

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Using 

TimeSeriesResample[{ts1, ts2}, "Intersection"] // ListLinePlot[#, Mesh -> Full] &

we obtain the values at common dates:

Blockquote

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