Date of Award

2024

Document Type

Dissertation

Degree Name

Doctor of Business Administration (DBA)

Department

School of Business

First Advisor

Dr. Paul Shelton

Second Advisor

Dr. Shawn Hussey

Third Advisor

Dr. Walker Orr

Abstract

This quantitative experiment executed an extensive study of the theoretical and exploratory development of a discrete step Federal Funds Target Rate (FFTR) forecast model expressed as the time series geometric average of an applied transform conversion of the U.S. Treasury Yield Curve (USTC). The novel approach, introduced as the Geometric Yield Curve (GYC) model, used USTC data taken directly from the U.S. Treasury Department website as its only input for term structure of interest rate modeling specific to the FFTR. A transform process, presented as term framing, introduced conversion of USTC embedded macroeconomic and macro-finance trend information into a daily single point time series plot. Then, GYC model time series output formed the basis for the further development of a discrete step FFTR forecast model. Three separate essays of quantitative study are included, one for each of the developmental phases of the GYC model. This study executed quantitative analysis along three test principles of FFTR forecast validity: (a) as a macro-finance forecast tool, (b) as a terminal FFTR forecast tool, and (c) as a sequential FFTR forecast tool. In the course of this analysis, specific quantitative tools and techniques were modified and developed for specified interest rate use cases within a controlled testing environment. The GYC model forecast performance exhibited quantitative viability as a working forecast tool at all three established test principle levels. This developmental work offers broad forecast analytic application through the lowest data acquisition cost, highest calculation efficiency, and relevant forecast output.

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