In this paper we present an application of statistics using real stock market data. Most, if not all, students have some familiarity with the stock market (or at least they have heard about it) and therefore can understand the problem easily. It is the real data analysis that students find interesting. Here we explore the building of efficient portfolios through optimization using examples of two and three stocks, and how covariance and correlation can help the investor to diversify his or her risk. We discuss why diversification works, but also the problems that arise in portfolio management. Stock market data can be incorporated at any level of statistics, from lower division, to upper division, to graduate courses of Mathematics and Statistics. From our experience, students find this topic very interesting and often they want to enroll in other courses related to this area.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education