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http://dx.doi.org/10.5351/KJAS.2014.27.4.577

Analyzing Financial Data from Banks and Savings Banks: Application of Bioinformatical Methods  

Pak, Ro Jin (Department of Applied Statistics, Dankook University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.4, 2014 , pp. 577-588 More about this Journal
Abstract
The collection and storage of a large volumes of data are becoming easier; however, the number of variables is sometimes more than the number of samples(objects). We now face the problem of dependency among variables(such as multicollinearity) due to the increased number of variables. We cannot apply various statistical methods without satisfying independency assumption. In order to overcome such a drawback we consider a categorizing (or discretizing) observations. We have a data set of nancial indices from banks in Korea that contain 78 variables from 16 banks. Genetic sequence data is also a good example of a large data and there have been numerous statistical methods to handle it. We discover lots of useful bank information after we transform bank data into categorical data that resembles genetic sequence data and apply bioinformatic techniques.
Keywords
clustering; multicollinearity; phylogenetic tree; sequence alignment;
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Times Cited By KSCI : 1  (Citation Analysis)
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