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Texas State University

Predicting Fraud vs Non-Fraud in Publicly Traded U.S. Companies Using Machine Learning Techniques

dc:creator Zaman, Tayafa

thesis:degree_name Master of Science

dc:date.issued2025

Abstract

dc:description.abstract

No abstract prepared.

Degree

thesis:*

Name thesis:degree_name: Master of Science
Level thesis:degree_level: Masters
Discipline thesis:degree_discipline: Quantitative Finance and Economics
Grantor: Texas State University
Year dc:date.issued: 2025

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Zaman, Tayafa
Advisor dc:contributor.advisor: Alanis, Emmanuel
Committee members dc:contributor.committeemember: Liu, Yifan
Payne, Janet

Subjects

dc:subject × 4

Rights

Language dc:language.iso: en

Identifiers

dc:identifier.*

Handle dc:identifier.uri: https://hdl.handle.net/10877/22111
OAI identifier oai:identifier: oai:digital.library.txst.edu:10877/22111

Chain of custody

source

Harvested from: Texas State University
Base URL: digital.library.txst.edu/server/oai/request
Last updated: 2026-07-27
Source record: OAI-PMH GetRecord

related terms

citation

Zaman, Tayafa. Predicting Fraud vs Non-Fraud in Publicly Traded U.S. Companies Using Machine Learning Techniques. Masters thesis, Texas State University, 2025. https://hdl.handle.net/10877/22111

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