Error when using interpolation method

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.

[Matt J]

What should it be doing that is different from the results shown above?

[Emad]

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]

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]

It is a sample from the whole results. The whole data is too large. Hopefully to aid me.

[Star Strider]

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]

The calculation thaI want to get after the interpolation is construct 5 minutes log-returns. That is the goal from the prepration data.

Answer 1

[Star Strider]

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.

.

[Emad]

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]

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]

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]

I am now completely lost.

I will delete my Answers in a few hours.

[Emad]

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]

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.