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