Thesis or dissertation
Date of this Version
The Millennial cohort has been subject to many generalities regarding their behaviors and preferences when considering investing their wealth. Through use of a factor analysis and k-means cluster segmentation, five distinct clusters of potential investors emerged, each unique in their activity (or lack thereof) towards their portfolios, as well as their desired investment horizon. These clusters further differed in their desire for a traditional financial advisor as opposed to emerging investment algorithms; namely, Cluster 2 prefers the conjunction of an experienced advisor with advanced algorithms as opposed to exclusive use of either option. Further, regarding degrees of control, each Cluster preferred a different degree of control (from Limited to Total) as well as abilities to Adjust or Change an algorithm’s parameters. Finally, upon examination of any mediating variables, such as degree of control on portfolio distribution, it was determined that very little statistical significance existed.
Finance, Investment, Decision Making, Consumer Choice, FinTech, Algorithms
Date Posted: 24 October 2018