Assessing the risk and returns of multiple firms can be difficult; grouping more than two hundred thirty equities in the Philippine stock market is nearly possible with the help of the clustering technique. Clu
% Done with input argument processing, begin clustering%dispfmt = '%6dt%6dt%8dt%12g';D = repmat(NaN,n,k); % point-to-cluster distancesDel = repmat(NaN,n,k); % reassignment criterionm = zeros(k,1);totsumDBest = Inf;for rep = 1:repsswitch start...
Based on these assumptions,the purpose of this paperis to perform a comparative analysis between the results of two well-known and frequently used clustering methods (K-Mean and K-Medoid) in the field of financial performance. The processing of databases with large and variable data is possible...
Based on these assumptions,the purpose of this paperis to perform a comparative analysis between the results of two well-known and frequently used clustering methods (K-Mean and K-Medoid) in the field of financial performance. The processing of databases with large and variable data is possible...