Degree Name

MS (Master of Science)

Program

Mathematical Sciences

Date of Award

5-2022

Committee Chair or Co-Chairs

JeanMarie Hendrickson

Committee Members

Nicole Lewis, Robert Price, Gary Shelley, Michele Joyner

Abstract

Statistical inference is a tool for creating models that can accurately display real-world events. Special importance is given to the financial methods that model risk and large price movements. A parameter that describes tail heaviness, and risk overall, is α. This research finds a representative distribution that models α. The absolute value of standardized stock returns from the Center for Research on Security Prices are used in this research. The inference is performed using R. Approximations for α are found using the ptsuite package. The GAMLSS package employs maximum likelihood estimation to estimate distribution parameters using the CRSP data. The distributions are selected by using AIC and worm plots. The Skew t family is found to be representative for the parameter α based on subsets of the CRSP data. The Skew t type 2 distribution is robust for multiple subsets of values calculated from the CRSP stock return data.

Document Type

Thesis - embargo

Copyright

Copyright by the authors.

Available for download on Thursday, June 15, 2023

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