JSM 2004 - Toronto

Abstract #300843

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Activity Number: 90
Type: Contributed
Date/Time: Monday, August 9, 2004 : 9:00 AM to 10:50 AM
Sponsor: Business and Economics Statistics Section
Abstract - #300843
Title: A Multivariate Statistical Analysis of Stock Trends
Author(s): James B. Lawrence*+ and April Kerby and Vasant Waikar
Companies: Miami University and Alma College and Miami University
Address: 208 Bishop Hall, Oxford, OH, 45056,
Keywords: discriminant ; analysis ; stocks
Abstract:

The stock market is a financial game of winners and losers. Is your stock tried and true or here today, gone tomorrow? How can one pick out a golden nugget like Microsoft from the hundreds of dot-coms that went bust after an all-too-brief moment of glory? It may seem like there is really no way to tell--a seemingly uncountable number of variables influence our markets and companies; how can one take all of them into account? Is there a simpler way of looking at the market madness? This paper seeks to use statistical methods to survey and analyze financial and economic data to discover such a method of simplification. Using principal component analysis, we will combine related factors into a smaller number of key components largely responsible for the variations observed. Then, using discriminant analysis, we will develop a model for separating companies into two categories based on their predicted stock performance: good and poor investment choices.

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