1Research Scholar, Shri Jairambhai Patel Institute of Business Management and Computer Applications, Gandhinagar382007, Gujarat, India
2Assistant Professor, Shri Jairambhai Patel Institute of Business Management and Computer Applications, Gandhinagar382007, Gujarat, India
3Research Guide, Faculty of Science R.K. University, Rajkot360020, Gujarat, India
4Director (I/C) and Associate Professor, Narmada College of Computer Application, Bharuch392011, Gujarat, India
*Corresponding author Email id: preeti.dalal@gmail.com
Clustering is one of the data mining techniques widely used in various application areas. It is a process of assigning data objects in different groups so that data objects in the same group have similar behaviour towards each other and be different from other objects in the other groups. It is also known as an unsupervised technique in which class label is not available. Clustering is one of the most popular data mining techniques used in various financial domains. In today's competitive financial market, investors want to earn profit from their investments. This paper shows detailed analysis of k-means clustering method using the Davies–Bouldin index to find the optimum number of clusters which is very difficult for this method. These clusters can be used in further investment analysis.
Clustering, Data Mining, Davies-Bouldin Index (DBI), Financial Ratio, k-means, Portfolio Management, Validity Index
