Stock Prices simulation and statistics

Hello, Please can someone help me with how to write a code to use the indices whose time are not more than 60 seconds from the attached different LSEs. Specifically, i am considering the different close prices from the different LSEs below.

%close prices in matrix 
nstock_val=[Close(1:30928,1) Close1(1:30928,1) Close2(1:30928,1) Close3(1:30928,1) Close4(1:30928,1)]; % reading the data
t = (Gmttime); % reading the data
time = datetime(t,'inputformat','dd.MM.yyyy HH:mm:ss.SSS');
LSE_matrix =log(nstock_val); %log of the datanstock_val=[Close(1:30928,1) Close1(1:30928,1) Close2(1:30928,1) Close3(1:30928,1) Close4(1:30928,1)]; % reading the data
I=1:(size(LSE_matrix,1)-1); % selecting the indices of all prices but the last time  when stock was opened
% data = time(:,1);
% id = [false; diff(time(:,1))> seconds(60)];%finds all row indices where the previous row
% %differs by more than 60 seconds
% data(id,:) = [];% deletes all data in those rows.
% time(id) = [];
I= I(diff(time(:,1)) <= seconds(60));
dLSE_col1 = LSE_matrix(I+1,1) - LSE_matrix(I,1);%  log difference
dLSE_col2 = LSE_matrix(I+1,2) - LSE_matrix(I,2);
dLSE_col3 = LSE_matrix(I+1,3) - LSE_matrix(I,3);
dLSE_col4 = LSE_matrix(I+1,4) - LSE_matrix(I,4);
dLSE_col5 = LSE_matrix(I+1,5) - LSE_matrix(I,5);
matrix_logdiff=[dLSE_col1 dLSE_col2 dLSE_col3 dLSE_col4 dLSE_col5];
nsample = floor((2/3)* length(matrix_logdiff)); %two thirds of the log
% difference of the data
 matrix_logdiff_nsample = matrix_logdiff(1:nsample,:);
 mean_vec = mean(matrix_logdiff_nsample); %finding the mean.
% 
 mean_vec = mean_vec';
% 
 cov_matrix = cov(matrix_logdiff_nsample); %the covariance
 dt=1;
%GBM parameter estimate
capbhat = sqrtm(cov_matrix./dt);    
ahat_vec  = (mean_vec/dt)+ diag((capbhat).^2)/2;
s0_vector =[nstock_val(nsample,1) nstock_val(nsample,2) nstock_val(nsample,3) nstock_val(nsample,4) nstock_val(nsample,5)];
s0_vector = s0_vector';