Publication Date

2024

Document Type

Dissertation/Thesis

First Advisor

Ryu, Duchwan

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Statistics and Actuarial Science

Abstract

The traditional two-pass regression to estimate risk premium has shortcomings. To get the correct asymptotic standard errors, we need to estimate both time-series regressions and cross-sectional regressions simultaneously. The Generalized Method of Moments (GMM) effectively addresses this issue by its nature fit of asset pricing model. In this paper, I re-examine the risk premium of Carhart’s four-factor model by integrating time-series and cross-sectional regressions within the GMM framework, which enhances the accuracy and reliability of the risk premium estimates.

Extent

32 pages

Language

en

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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