Date of Graduation
5-2023
Document Type
Thesis
Degree Name
Bachelor of Science
Degree Level
Undergraduate
Department
Finance
Advisor/Mentor
Rennie, Craig G.
Abstract
The objective of this study is to explore the use of well-researched market anomalies to generate higher risk-adjusted returns than the overall stock market. Four specific market anomalies are examined: the small-firm effect; price reversals; the January effect; and the momentum effect. It focuses on historical evidence, anomaly characteristics, and potential risks. This study also explores the use of anomaly detection techniques, such as machine learning, in identifying market mispricings. It finds that a selective approach, combining market anomalies with traditional investment strategies, is crucial for effective implementation. This study provides insights for investors seeking to capitalize on market anomalies to achieve higher risk-adjusted returns.
Keywords
market anomalies; portfolio management; outperforming the stock market
Citation
Bennett, B. (2023). Outperforming the Stock Market Using Market Anomalies. Finance Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/finnuht/98
