Error when using interpolation method

2023 10 月 28
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2023 10 月 29 に更新
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Ran in:

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Ran in:
Dears,
I have a dataset, includes variables serial, year, month, day, second, and price. I want to calculate the 5 minute frequency, using last tick interpolation. When I reaech to the last step, the serial numbers are changed. The codes here are provided by Star Strider.
T1 = readtable('Data.txt');
% (1) is the serial, (2) year, (3) month, (4) days, (5) time in seconds, and (6) price
T1.Properties.VariableNames = {'serial','year','month','day','seconds','price'}
T1 = 9123×6 table
serial year month day seconds price ______ ____ _____ ___ _______ ______ 1972 2013 7 31 1 168.98 1972 2013 7 31 2 169 1972 2013 7 31 3 169 1972 2013 7 31 4 168.99 1972 2013 7 31 5 168.98 1972 2013 7 31 6 168.98 1972 2013 7 31 7 168.98 1972 2013 7 31 8 168.98 1972 2013 7 31 9 168.99 1972 2013 7 31 10 168.98 1972 2013 7 31 11 168.97 1972 2013 7 31 12 168.97 1972 2013 7 31 13 168.98 1972 2013 7 31 14 168.97 1972 2013 7 31 16 168.97 1972 2013 7 31 17 168.96
% T1(end-4:end,:)
DT = datetime(T1{:,[2 3 4]}) + seconds(T1{:,5});
T2 = table(DT,T1{:,1},T1{:,6}, 'VariableNames',{'time','serial','price'})
T2 = 9123×3 table
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:01 1972 168.98 31-Jul-2013 00:00:02 1972 169 31-Jul-2013 00:00:03 1972 169 31-Jul-2013 00:00:04 1972 168.99 31-Jul-2013 00:00:05 1972 168.98 31-Jul-2013 00:00:06 1972 168.98 31-Jul-2013 00:00:07 1972 168.98 31-Jul-2013 00:00:08 1972 168.98 31-Jul-2013 00:00:09 1972 168.99 31-Jul-2013 00:00:10 1972 168.98 31-Jul-2013 00:00:11 1972 168.97 31-Jul-2013 00:00:12 1972 168.97 31-Jul-2013 00:00:13 1972 168.98 31-Jul-2013 00:00:14 1972 168.97 31-Jul-2013 00:00:16 1972 168.97 31-Jul-2013 00:00:17 1972 168.96
TT2 = table2timetable(T2);
TT2 = retime(TT2,'regular','linear','Timestep',minutes(5))
TT2 = 79×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:00 1972 168.96 31-Jul-2013 00:05:00 1972 169.19 31-Jul-2013 00:10:00 1972 169.11 31-Jul-2013 00:15:00 1972 169.04 31-Jul-2013 00:20:00 1972 169.19 31-Jul-2013 00:25:00 1972 169.05 31-Jul-2013 00:30:00 1972 169.14 31-Jul-2013 00:35:00 1972 169.09 31-Jul-2013 00:40:00 1972 169.04 31-Jul-2013 00:45:00 1972 169.06 31-Jul-2013 00:50:00 1972 169.13 31-Jul-2013 00:55:00 1972 169.11 31-Jul-2013 01:00:00 1972 169.45 31-Jul-2013 01:05:00 1972 169.41 31-Jul-2013 01:10:00 1972 169.57 31-Jul-2013 01:15:00 1972 169.56
A simple and results that I got is attached. Could you guide me to get the code accurately.

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Matt J
Matt J 2023 年 10 月 28 日
What should it be doing that is different from the results shown above?
Emad
Emad 2023 年 10 月 28 日
編集済み: Emad 2023 年 10 月 28 日
in the results (see the attached file) the serial numbers are changed, therefore, whether there is a misstake in the code, or any modifications that should be done?
Matt J
Matt J 2023 年 10 月 28 日
編集済み: Matt J 2023 年 10 月 28 日
But the data in Result.txt clearly doesn't come from the code you've posted. We can see the output of the code above, and the serial number is 1972 throughout.
Emad
Emad 2023 年 10 月 28 日
It is a sample from the whole results. The whole data is too large. Hopefully to aid me.
Star Strider
Star Strider 2023 年 10 月 28 日
What calculation is necessary to produce the result you want?
I suspect that whatever calculation is is being appliied to the price is being applied to the serial numbers as well, and that is the reason they are changing. The serial numbers probably only need to be interpolated to match the five-minute intervals, and not have any calculations applied to them.
Emad
Emad 2023 年 10 月 28 日
The calculation thaI want to get after the interpolation is construct 5 minutes log-returns. That is the goal from the prepration data.

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Star Strider
Star Strider 2023 年 10 月 28 日
編集済み: Star Strider 2023 年 10 月 28 日
Ran in:

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Ran in:
The serial numbers change position because timetable arrays require that the time vector be the first column, regardless of how the original table was constructed.
The serial numbers themselves do not change. (If they were included in the computations, one approach would simply be to remove them, calculate the timetable, and then re-insert them afterwards, interpolated separately to create an appropriate lrow size. However here they are simply interpolated, since that is all this code does.)
Example —
T1 = readtable('Data.txt');
% (1) is the serial, (2) year, (3) month, (4) days, (5) time in seconds, and (6) price
T1.Properties.VariableNames = {'serial','year','month','day','seconds','price'}
T1 = 9123×6 table
serial year month day seconds price ______ ____ _____ ___ _______ ______ 1972 2013 7 31 1 168.98 1972 2013 7 31 2 169 1972 2013 7 31 3 169 1972 2013 7 31 4 168.99 1972 2013 7 31 5 168.98 1972 2013 7 31 6 168.98 1972 2013 7 31 7 168.98 1972 2013 7 31 8 168.98 1972 2013 7 31 9 168.99 1972 2013 7 31 10 168.98 1972 2013 7 31 11 168.97 1972 2013 7 31 12 168.97 1972 2013 7 31 13 168.98 1972 2013 7 31 14 168.97 1972 2013 7 31 16 168.97 1972 2013 7 31 17 168.96
% T1(end-4:end,:)
DT = datetime(T1{:,[2 3 4]}) + seconds(T1{:,5});
% T2 = table(DT,T1{:,1},T1{:,6}, 'VariableNames',{'time','serial','price'})
T2 = table(T1{:,1},DT,T1{:,6}, 'VariableNames',{'serial','time','price'})
T2 = 9123×3 table
serial time price ______ ____________________ ______ 1972 31-Jul-2013 00:00:01 168.98 1972 31-Jul-2013 00:00:02 169 1972 31-Jul-2013 00:00:03 169 1972 31-Jul-2013 00:00:04 168.99 1972 31-Jul-2013 00:00:05 168.98 1972 31-Jul-2013 00:00:06 168.98 1972 31-Jul-2013 00:00:07 168.98 1972 31-Jul-2013 00:00:08 168.98 1972 31-Jul-2013 00:00:09 168.99 1972 31-Jul-2013 00:00:10 168.98 1972 31-Jul-2013 00:00:11 168.97 1972 31-Jul-2013 00:00:12 168.97 1972 31-Jul-2013 00:00:13 168.98 1972 31-Jul-2013 00:00:14 168.97 1972 31-Jul-2013 00:00:16 168.97 1972 31-Jul-2013 00:00:17 168.96
T2(end-4:end,:)
ans = 5×3 table
serial time price ______ ____________________ ______ 1972 31-Jul-2013 06:29:56 168.65 1972 31-Jul-2013 06:29:57 168.61 1972 31-Jul-2013 06:29:58 168.63 1972 31-Jul-2013 06:29:59 168.62 1972 31-Jul-2013 06:30:00 168.65
TT2 = table2timetable(T2)
TT2 = 9123×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:01 1972 168.98 31-Jul-2013 00:00:02 1972 169 31-Jul-2013 00:00:03 1972 169 31-Jul-2013 00:00:04 1972 168.99 31-Jul-2013 00:00:05 1972 168.98 31-Jul-2013 00:00:06 1972 168.98 31-Jul-2013 00:00:07 1972 168.98 31-Jul-2013 00:00:08 1972 168.98 31-Jul-2013 00:00:09 1972 168.99 31-Jul-2013 00:00:10 1972 168.98 31-Jul-2013 00:00:11 1972 168.97 31-Jul-2013 00:00:12 1972 168.97 31-Jul-2013 00:00:13 1972 168.98 31-Jul-2013 00:00:14 1972 168.97 31-Jul-2013 00:00:16 1972 168.97 31-Jul-2013 00:00:17 1972 168.96
TT2 = retime(TT2,'regular','linear','Timestep',minutes(5))
TT2 = 79×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:00 1972 168.96 31-Jul-2013 00:05:00 1972 169.19 31-Jul-2013 00:10:00 1972 169.11 31-Jul-2013 00:15:00 1972 169.04 31-Jul-2013 00:20:00 1972 169.19 31-Jul-2013 00:25:00 1972 169.05 31-Jul-2013 00:30:00 1972 169.14 31-Jul-2013 00:35:00 1972 169.09 31-Jul-2013 00:40:00 1972 169.04 31-Jul-2013 00:45:00 1972 169.06 31-Jul-2013 00:50:00 1972 169.13 31-Jul-2013 00:55:00 1972 169.11 31-Jul-2013 01:00:00 1972 169.45 31-Jul-2013 01:05:00 1972 169.41 31-Jul-2013 01:10:00 1972 169.57 31-Jul-2013 01:15:00 1972 169.56
TT2(end-4:end,:)
ans = 5×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 06:10:00 1972 169.12 31-Jul-2013 06:15:00 1972 168.85 31-Jul-2013 06:20:00 1972 168.7 31-Jul-2013 06:25:00 1972 168.51 31-Jul-2013 06:30:00 1972 168.65
T3 = readtable('Result.txt') % Second File
T3 = 865×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ____ ______ {''03-Jan-2005'} {'00:00:00''} 1 121.56 {''03-Jan-2005'} {'00:05:00''} 1 121.64 {''03-Jan-2005'} {'00:10:00''} 1 121.69 {''03-Jan-2005'} {'00:15:00''} 1 121.65 {''03-Jan-2005'} {'00:20:00''} 1 121.65 {''03-Jan-2005'} {'00:25:00''} 1 121.51 {''03-Jan-2005'} {'00:30:00''} 1 121.51 {''03-Jan-2005'} {'00:35:00''} 1 121.29 {''03-Jan-2005'} {'00:40:00''} 1 121.18 {''03-Jan-2005'} {'00:45:00''} 1 121.15 {''03-Jan-2005'} {'00:50:00''} 1 120.99 {''03-Jan-2005'} {'00:55:00''} 1 120.98 {''03-Jan-2005'} {'01:00:00''} 1 120.98 {''03-Jan-2005'} {'01:05:00''} 1 120.92 {''03-Jan-2005'} {'01:10:00''} 1 120.82 {''03-Jan-2005'} {'01:15:00''} 1 120.8
T3(end-4:end,:)
ans = 5×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ______ ______ {''05-Jan-2005'} {'23:40:00''} 3.9809 118.44 {''05-Jan-2005'} {'23:45:00''} 3.9857 118.44 {''05-Jan-2005'} {'23:50:00''} 3.9904 118.44 {''05-Jan-2005'} {'23:55:00''} 3.9952 118.44 {''06-Jan-2005'} {'00:00:00''} 3.9999 118.44
Time = datetime(T3.Var1, 'InputFormat','''''dd-MMM-yyyy') + timeofday(datetime(T3.Var2,'InputFormat','HH:mm:ss'''''));
T3 = removevars(T3,[1 2]);
T3 = addvars(T3, Time,'Before','Var3')
T3 = 865×3 table
Time Var3 Var4 ____________________ ____ ______ 03-Jan-2005 00:00:00 1 121.56 03-Jan-2005 00:05:00 1 121.64 03-Jan-2005 00:10:00 1 121.69 03-Jan-2005 00:15:00 1 121.65 03-Jan-2005 00:20:00 1 121.65 03-Jan-2005 00:25:00 1 121.51 03-Jan-2005 00:30:00 1 121.51 03-Jan-2005 00:35:00 1 121.29 03-Jan-2005 00:40:00 1 121.18 03-Jan-2005 00:45:00 1 121.15 03-Jan-2005 00:50:00 1 120.99 03-Jan-2005 00:55:00 1 120.98 03-Jan-2005 01:00:00 1 120.98 03-Jan-2005 01:05:00 1 120.92 03-Jan-2005 01:10:00 1 120.82 03-Jan-2005 01:15:00 1 120.8
T3(end-4:end,:)
ans = 5×3 table
Time Var3 Var4 ____________________ ______ ______ 05-Jan-2005 23:40:00 3.9809 118.44 05-Jan-2005 23:45:00 3.9857 118.44 05-Jan-2005 23:50:00 3.9904 118.44 05-Jan-2005 23:55:00 3.9952 118.44 06-Jan-2005 00:00:00 3.9999 118.44
The second file (‘Result.txt’) appears to be entirely different form the first. The variables are not defined, so I have no idea what they are.
.

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Emad
Emad 2023 年 10 月 28 日
The results file is from what I got, i do not know why there are 4 variables, and we only use 3. In this comment I will post the code and the files again to you. What I want to solve is why serial is included in the calculation. As a result the numbers changed.
These are the codes that I used:
T1 = readtable('Data.txt');
T1.Properties.VariableNames = {'Serial','Year','Month','Day','Seconds','Price'};
DT = datetime(T1{:,[2 3 4]}) + seconds(T1{:,5});
T2 = table(DT,T1{:,1},T1{:,6}, 'VariableNames',{'Time','Serial','Price'});
TT2 = table2timetable(T2);
To this step the Serial is ok, and everything is right.
When I use this code,
TT2 = retime(TT2,'regular','linear','Timestep',minutes(5));
The Serial numbers are changed. What I need is to get the reuslts such as in TT2, but the Serial numbers remain.
Star Strider
Star Strider 2023 年 10 月 28 日
編集済み: Star Strider 2023 年 10 月 28 日
Ran in:
Ran in:
My code resamples the timetables using interpolation.
What sort of calculation do you want to use, since that is apparently the objective here. I never heard of what you previously posted so I have no idea how to code it. You need to explain that calculation.
EDIT — (28 Oct 2023 at 21:48)
Apparently, ‘log return’ is:
Then this should work —
T1 = readtable('Data.txt');
% (1) is the serial, (2) year, (3) month, (4) days, (5) time in seconds, and (6) price
T1.Properties.VariableNames = {'serial','year','month','day','seconds','price'}
T1 = 9123×6 table
serial year month day seconds price ______ ____ _____ ___ _______ ______ 1972 2013 7 31 1 168.98 1972 2013 7 31 2 169 1972 2013 7 31 3 169 1972 2013 7 31 4 168.99 1972 2013 7 31 5 168.98 1972 2013 7 31 6 168.98 1972 2013 7 31 7 168.98 1972 2013 7 31 8 168.98 1972 2013 7 31 9 168.99 1972 2013 7 31 10 168.98 1972 2013 7 31 11 168.97 1972 2013 7 31 12 168.97 1972 2013 7 31 13 168.98 1972 2013 7 31 14 168.97 1972 2013 7 31 16 168.97 1972 2013 7 31 17 168.96
% T1(end-4:end,:)
DT = datetime(T1{:,[2 3 4]}) + seconds(T1{:,5});
T2 = table(DT,T1{:,1},T1{:,6}, 'VariableNames',{'time','serial','price'})
T2 = 9123×3 table
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:01 1972 168.98 31-Jul-2013 00:00:02 1972 169 31-Jul-2013 00:00:03 1972 169 31-Jul-2013 00:00:04 1972 168.99 31-Jul-2013 00:00:05 1972 168.98 31-Jul-2013 00:00:06 1972 168.98 31-Jul-2013 00:00:07 1972 168.98 31-Jul-2013 00:00:08 1972 168.98 31-Jul-2013 00:00:09 1972 168.99 31-Jul-2013 00:00:10 1972 168.98 31-Jul-2013 00:00:11 1972 168.97 31-Jul-2013 00:00:12 1972 168.97 31-Jul-2013 00:00:13 1972 168.98 31-Jul-2013 00:00:14 1972 168.97 31-Jul-2013 00:00:16 1972 168.97 31-Jul-2013 00:00:17 1972 168.96
T2(end-4:end,:)
ans = 5×3 table
time serial price ____________________ ______ ______ 31-Jul-2013 06:29:56 1972 168.65 31-Jul-2013 06:29:57 1972 168.61 31-Jul-2013 06:29:58 1972 168.63 31-Jul-2013 06:29:59 1972 168.62 31-Jul-2013 06:30:00 1972 168.65
TT2 = table2timetable(T2)
TT2 = 9123×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:01 1972 168.98 31-Jul-2013 00:00:02 1972 169 31-Jul-2013 00:00:03 1972 169 31-Jul-2013 00:00:04 1972 168.99 31-Jul-2013 00:00:05 1972 168.98 31-Jul-2013 00:00:06 1972 168.98 31-Jul-2013 00:00:07 1972 168.98 31-Jul-2013 00:00:08 1972 168.98 31-Jul-2013 00:00:09 1972 168.99 31-Jul-2013 00:00:10 1972 168.98 31-Jul-2013 00:00:11 1972 168.97 31-Jul-2013 00:00:12 1972 168.97 31-Jul-2013 00:00:13 1972 168.98 31-Jul-2013 00:00:14 1972 168.97 31-Jul-2013 00:00:16 1972 168.97 31-Jul-2013 00:00:17 1972 168.96
TT2 = retime(TT2,'regular','linear','Timestep',minutes(5))
TT2 = 79×2 timetable
time serial price ____________________ ______ ______ 31-Jul-2013 00:00:00 1972 168.96 31-Jul-2013 00:05:00 1972 169.19 31-Jul-2013 00:10:00 1972 169.11 31-Jul-2013 00:15:00 1972 169.04 31-Jul-2013 00:20:00 1972 169.19 31-Jul-2013 00:25:00 1972 169.05 31-Jul-2013 00:30:00 1972 169.14 31-Jul-2013 00:35:00 1972 169.09 31-Jul-2013 00:40:00 1972 169.04 31-Jul-2013 00:45:00 1972 169.06 31-Jul-2013 00:50:00 1972 169.13 31-Jul-2013 00:55:00 1972 169.11 31-Jul-2013 01:00:00 1972 169.45 31-Jul-2013 01:05:00 1972 169.41 31-Jul-2013 01:10:00 1972 169.57 31-Jul-2013 01:15:00 1972 169.56
% Calculate & Add 'Log Return' Variable To 'TT2' —
LogRet(1) = NaN;
for k = 2:size(TT2,1)
LogRet(k,:) = log(TT2.price(k)/TT2.price(k-1));
end
TT2 = addvars(TT2, LogRet)
TT2 = 79×3 timetable
time serial price LogRet ____________________ ______ ______ ___________ 31-Jul-2013 00:00:00 1972 168.96 NaN 31-Jul-2013 00:05:00 1972 169.19 0.0013603 31-Jul-2013 00:10:00 1972 169.11 -0.00048774 31-Jul-2013 00:15:00 1972 169.04 -0.00039923 31-Jul-2013 00:20:00 1972 169.19 0.00088697 31-Jul-2013 00:25:00 1972 169.05 -0.00082781 31-Jul-2013 00:30:00 1972 169.14 0.00053225 31-Jul-2013 00:35:00 1972 169.09 -0.00028087 31-Jul-2013 00:40:00 1972 169.04 -0.00031053 31-Jul-2013 00:45:00 1972 169.06 0.00011091 31-Jul-2013 00:50:00 1972 169.13 0.00042136 31-Jul-2013 00:55:00 1972 169.11 -0.00014191 31-Jul-2013 01:00:00 1972 169.45 0.0020322 31-Jul-2013 01:05:00 1972 169.41 -0.00023609 31-Jul-2013 01:10:00 1972 169.57 0.00094401 31-Jul-2013 01:15:00 1972 169.56 -2.9487e-05
TT2(end-4:end,:)
ans = 5×3 timetable
time serial price LogRet ____________________ ______ ______ ___________ 31-Jul-2013 06:10:00 1972 169.12 1.971e-05 31-Jul-2013 06:15:00 1972 168.85 -0.0015978 31-Jul-2013 06:20:00 1972 168.7 -0.00088876 31-Jul-2013 06:25:00 1972 168.51 -0.0011269 31-Jul-2013 06:30:00 1972 168.65 0.00083047
% --------------------------------------------------------------------------------
T3 = readtable('Result.txt') % Second File
T3 = 865×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ____ ______ {''03-Jan-2005'} {'00:00:00''} 1 121.56 {''03-Jan-2005'} {'00:05:00''} 1 121.64 {''03-Jan-2005'} {'00:10:00''} 1 121.69 {''03-Jan-2005'} {'00:15:00''} 1 121.65 {''03-Jan-2005'} {'00:20:00''} 1 121.65 {''03-Jan-2005'} {'00:25:00''} 1 121.51 {''03-Jan-2005'} {'00:30:00''} 1 121.51 {''03-Jan-2005'} {'00:35:00''} 1 121.29 {''03-Jan-2005'} {'00:40:00''} 1 121.18 {''03-Jan-2005'} {'00:45:00''} 1 121.15 {''03-Jan-2005'} {'00:50:00''} 1 120.99 {''03-Jan-2005'} {'00:55:00''} 1 120.98 {''03-Jan-2005'} {'01:00:00''} 1 120.98 {''03-Jan-2005'} {'01:05:00''} 1 120.92 {''03-Jan-2005'} {'01:10:00''} 1 120.82 {''03-Jan-2005'} {'01:15:00''} 1 120.8
T3(end-4:end,:)
ans = 5×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ______ ______ {''05-Jan-2005'} {'23:40:00''} 3.9809 118.44 {''05-Jan-2005'} {'23:45:00''} 3.9857 118.44 {''05-Jan-2005'} {'23:50:00''} 3.9904 118.44 {''05-Jan-2005'} {'23:55:00''} 3.9952 118.44 {''06-Jan-2005'} {'00:00:00''} 3.9999 118.44
Time = datetime(T3.Var1, 'InputFormat','''''dd-MMM-yyyy') + timeofday(datetime(T3.Var2,'InputFormat','HH:mm:ss'''''));
T3 = removevars(T3,[1 2]);
T3 = addvars(T3, Time,'Before','Var3')
T3 = 865×3 table
Time Var3 Var4 ____________________ ____ ______ 03-Jan-2005 00:00:00 1 121.56 03-Jan-2005 00:05:00 1 121.64 03-Jan-2005 00:10:00 1 121.69 03-Jan-2005 00:15:00 1 121.65 03-Jan-2005 00:20:00 1 121.65 03-Jan-2005 00:25:00 1 121.51 03-Jan-2005 00:30:00 1 121.51 03-Jan-2005 00:35:00 1 121.29 03-Jan-2005 00:40:00 1 121.18 03-Jan-2005 00:45:00 1 121.15 03-Jan-2005 00:50:00 1 120.99 03-Jan-2005 00:55:00 1 120.98 03-Jan-2005 01:00:00 1 120.98 03-Jan-2005 01:05:00 1 120.92 03-Jan-2005 01:10:00 1 120.82 03-Jan-2005 01:15:00 1 120.8
T3(end-4:end,:)
ans = 5×3 table
Time Var3 Var4 ____________________ ______ ______ 05-Jan-2005 23:40:00 3.9809 118.44 05-Jan-2005 23:45:00 3.9857 118.44 05-Jan-2005 23:50:00 3.9904 118.44 05-Jan-2005 23:55:00 3.9952 118.44 06-Jan-2005 00:00:00 3.9999 118.44
% --------------------------------------------------------------------------------
T3 = readtable('after the last code.txt')
T3 = 2880×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ____ ______ {''03-Jan-2005'} {'00:00:00''} 1 121.56 {''03-Jan-2005'} {'00:05:00''} 1 121.64 {''03-Jan-2005'} {'00:10:00''} 1 121.69 {''03-Jan-2005'} {'00:15:00''} 1 121.65 {''03-Jan-2005'} {'00:20:00''} 1 121.65 {''03-Jan-2005'} {'00:25:00''} 1 121.51 {''03-Jan-2005'} {'00:30:00''} 1 121.51 {''03-Jan-2005'} {'00:35:00''} 1 121.29 {''03-Jan-2005'} {'00:40:00''} 1 121.18 {''03-Jan-2005'} {'00:45:00''} 1 121.15 {''03-Jan-2005'} {'00:50:00''} 1 120.99 {''03-Jan-2005'} {'00:55:00''} 1 120.98 {''03-Jan-2005'} {'01:00:00''} 1 120.98 {''03-Jan-2005'} {'01:05:00''} 1 120.92 {''03-Jan-2005'} {'01:10:00''} 1 120.82 {''03-Jan-2005'} {'01:15:00''} 1 120.8
T4 = readtable('after the last code.txt')
T4 = 2880×4 table
Var1 Var2 Var3 Var4 ________________ _____________ ____ ______ {''03-Jan-2005'} {'00:00:00''} 1 121.56 {''03-Jan-2005'} {'00:05:00''} 1 121.64 {''03-Jan-2005'} {'00:10:00''} 1 121.69 {''03-Jan-2005'} {'00:15:00''} 1 121.65 {''03-Jan-2005'} {'00:20:00''} 1 121.65 {''03-Jan-2005'} {'00:25:00''} 1 121.51 {''03-Jan-2005'} {'00:30:00''} 1 121.51 {''03-Jan-2005'} {'00:35:00''} 1 121.29 {''03-Jan-2005'} {'00:40:00''} 1 121.18 {''03-Jan-2005'} {'00:45:00''} 1 121.15 {''03-Jan-2005'} {'00:50:00''} 1 120.99 {''03-Jan-2005'} {'00:55:00''} 1 120.98 {''03-Jan-2005'} {'01:00:00''} 1 120.98 {''03-Jan-2005'} {'01:05:00''} 1 120.92 {''03-Jan-2005'} {'01:10:00''} 1 120.82 {''03-Jan-2005'} {'01:15:00''} 1 120.8
Do the same thing with other files, if desired.
.
Emad
Emad 2023 年 10 月 28 日
編集済み: Emad 2023 年 10 月 28 日
Thanks for the code and your efforts. I really appreciate it. For the interpolation, as I want to use the last tick interpolation. In other words, if the price at second 600 is not available, we can use the price at second 595 not 602. This what I want to get in the interpolation. I'm not sure whether the "linear" do this or not. Also these should be separated among serial numbers. prices for serial number 2 separte from serial number 1 and so on.
Star Strider
Star Strider 2023 年 10 月 28 日
I am now completely lost.
I will delete my Answers in a few hours.
Emad
Emad 2023 年 10 月 28 日
I really benefit from your codes, you nearly right in most of it. What I want to check, is the interpolation method, as I want to get the last tick. I explain it in the previous replay.
Star Strider
Star Strider 2023 年 10 月 29 日
Thank you!
The last tick would be:
Last = T2(end,:)
or:
Last = TT2(end,:)
depending on what you want.
The same approach works for any of the other table or timetable arrays.

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Emad
Emad
2023 年 10 月 28 日

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Star Strider
Star Strider
2023 年 10 月 29 日

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