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Abstract Details

Activity Number: 574
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract - #304174
Title: Utilizing ARC Length to Cluster Stocks According to Risk
Author(s): Ferebee Tunno*+ and Tharanga Wickramarachchi
Companies: Arkansas State University and Clemson University
Address: 1001 N Patrick Street, Jonesboro, AR, 72401-8779, United States
Keywords: arc length ; cluster ; k-means++ ; stocks

In finance, there has always been an interest in finding meaningful ways to cluster stocks. Oftentimes, an economist will partition a collection of stocks into subsets according to their volatility in order to sort the safer stocks from the more risky ones. This talk presents a new way to cluster stocks via risk/volatility by utilizing the measure of arc length, followed by an application involving thirty popular stocks.

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