Hi I am working on similarity measure on the different assets classification. I have close to 12 assets classes for more than 50 banks spanning from 2000Q1-4 -2019Q1-4 for each assets class. I am interested in calculating the similarity measure amongst each asset class using the Jaccard measure and i do not know how, is there anyone that can help with a clue or a guide. My data sets has been reshaped wide. BANKID represents the each banks, while each assets class is defined by the quarter period.
BANKID cash_bal2000Q1 securities2000Q1 fedfnd_revrepo2000Q1 loan_lease_hfs2000Q1 Joint-venture2000Q1 other assets2000Q1 TradingAssets2000Q1 IntangibleAssets2000Q1 otherrealestate2000Q1 securities2000Q1 fixedassets2000Q1 net-loans2000Q1
100003 0.0523267 0.3282848 0.0035845 0.0051423 0.0035845 0.0523267 0.3282848 0.0035845 0.0051423 0.0035845 0.0523267 0.0035845
100134 0.023778 0.2791913 0.0038878 0 0.0038878 0.023778 0.2791913 0.0038878 0 0.0038878 0.023778 0.0038878
100135 0.0230704 0.2506895 0.00654 0.000572 0.00654 0.0230704 0.2506895 0.00654 0.000572 0.00654 0.0230704 0.00654
100144 0.1323925 0.0914672 0.0345783 0 0.0345783 0.1323925 0.0914672 0.0345783 0 0.0345783 0.1323925 0.0345783
100154 0.0534938 0.0709148 0.0026255 0.0053682 0.0026255 0.0534938 0.0709148 0.0026255 0.0053682 0.0026255 0.0534938 0.0026255
100161 0.0506434 0.2294578 0.0018176 0.0080809 0.0018176 0.0506434 0.2294578 0.0018176 0.0080809 0.0018176 0.0506434 0.0018176
100165 0.0256106 0.2885543 0.0335942 0.0220141 0.0335942 0.0256106 0.2885543 0.0335942 0.0220141 0.0335942 0.0256106 0.0335942
100173 0.0333732 0.2799982 0.0094496 0 0.0094496 0.0333732 0.2799982 0.0094496 0 0.0094496 0.0333732 0.0094496
100184 0.0518307 0.2053013 0.0196109 0.0006451 0.0196109 0.0518307 0.2053013 0.0196109 0.0006451 0.0196109 0.0518307 0.0196109
100185 0.0379655 0.3561531 0.004141 0.0001412 0.004141 0.0379655 0.3561531 0.004141 0.0001412 0.004141 0.0379655 0.004141
100196 0.0873589 0.2289798 0.0161368 0.0026473 0.0161368 0.0873589 0.2289798 0.0161368 0.0026473 0.0161368 0.0873589 0.0161368