John, I'll assume you have the Financial Toolbox. I think what you're looking to do is to calculate mean price, by ticker and week, with the exemplar date for each week being the last business day. There are several ways you could do that. Since you already have a table, varfun is one easy way.
First cook up some fake data.
>> Date = datetime(2016,3,[22;23;24;28;29;21;22;23;24;28;29],'Format','eee dd-MMM-yyyy');
>> Ticker = categorical({'A'; 'A'; 'A'; 'A'; 'A'; 'B'; 'B'; 'B'; 'B'; 'B'; 'B'});
>> Price = rand(size(Ticker));
>> TS = table(Date,Ticker,Price)
TS =
Date Ticker Price
_______________ ______ ________
Tue 22-Mar-2016 A 0.13197
Wed 23-Mar-2016 A 0.94205
Thu 24-Mar-2016 A 0.95613
Mon 28-Mar-2016 A 0.57521
Tue 29-Mar-2016 A 0.05978
Mon 21-Mar-2016 B 0.23478
Tue 22-Mar-2016 B 0.35316
Wed 23-Mar-2016 B 0.82119
Thu 24-Mar-2016 B 0.015403
Mon 28-Mar-2016 B 0.043024
Tue 29-Mar-2016 B 0.16899
Now find the last business day in each week, by first finding the end of the week and then stepping back.
>> hol = holidays(datetime(2016,1,1),datetime(2016,12,31))
>> EOWDate = dateshift(TS.Date,'end','week');
>> TS.BusDate = busdate(EOWDate,'previous',hol);
>> TS.BusDate.Format = ['eee ' TS.BusDate.Format]
TS =
Date Ticker Price BusDate
_______________ ______ _______ ___________________
Tue 22-Mar-2016 A 0.64912 Thu Thu 24-Mar-2016
Wed 23-Mar-2016 A 0.73172 Thu Thu 24-Mar-2016
Thu 24-Mar-2016 A 0.64775 Thu Thu 24-Mar-2016
Mon 28-Mar-2016 A 0.45092 Fri Fri 01-Apr-2016
Tue 29-Mar-2016 A 0.54701 Fri Fri 01-Apr-2016
Mon 21-Mar-2016 B 0.29632 Thu Thu 24-Mar-2016
Tue 22-Mar-2016 B 0.74469 Thu Thu 24-Mar-2016
Wed 23-Mar-2016 B 0.18896 Thu Thu 24-Mar-2016
Thu 24-Mar-2016 B 0.68678 Thu Thu 24-Mar-2016
Mon 28-Mar-2016 B 0.18351 Fri Fri 01-Apr-2016
Tue 29-Mar-2016 B 0.36848 Fri Fri 01-Apr-2016
Finally, apply mean to the prices, grouping by ticker and week.
>> varfun(@mean,TS,'GroupingVariables',{'Ticker' 'BusDate'},'InputVariables','Price')
ans =
Ticker BusDate GroupCount mean_Price
______ ___________ __________ __________
A 24-Mar-2016 3 0.67672
A 01-Apr-2016 2 0.31749
B 24-Mar-2016 4 0.35613
B 01-Apr-2016 2 0.10601
Best Answer