Unraveling market mysteries: a comprehensive review of financial anomalies and puzzles [version 1; peer review: 1 approved with reservations]

Osterrieder, Jörg Robert; Seigne, Michael (2023). Unraveling market mysteries: a comprehensive review of financial anomalies and puzzles [version 1; peer review: 1 approved with reservations] Open Research Europe, 3(172) F1000 Research https://doi.org/10.12688/openreseurope.16436.1

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This comprehensive literature review consolidates various market anomalies and puzzles, providing an aggregated perspective to understand these complex dynamics that challenge the traditional Efficient Market Hypothesis. We examined numerous academic works to reveal insights into long-term return irregularities, earnings management influence on equity offerings, and information uncertainty’s impact on stock returns. The review delves into unique phenomena like persistent mutual fund performance, the day-of-the-week returns, the January effect, weather-induced mood shifts on the market, and the dynamics of multiple anomalies. International asset pricing and weekend anomalies were also discussed, with a particular focus on cryptocurrency efficiency. Incorporating behavioral finance perspectives, we explored social transmission bias, emotional finance, biased beliefs, investor optimism, sentiment, and global market inefficiencies. The influence of unique events and seasonal factors, such as the Super Bowl, daylight saving time, and the Halloween effect, were also analyzed. The review concludes by highlighting the evolving landscape of market anomalies, discussing ma- chine learning approaches to anomaly research, investor behavior challenges, and the disappearing anomalies in country and industry returns. It sets the groundwork for holistic comprehension of market anomalies, suggesting future research directions such as exploring new data sources, comprehensive theoretical modeling, and the role of technology, market regulations, and environmental changes on market anomalies.

Item Type:	Journal Article (Original Article)
Division/Institute:	Business School > Institute for Applied Data Science & Finance Business School > Institute for Applied Data Science & Finance > Finance, Accounting and Tax Business School
Name:	Osterrieder, Jörg Robert0000-0003-0189-8636 and Seigne, Michael
Subjects:	H Social Sciences > HG Finance
ISSN:	2732-5121
Publisher:	F1000 Research
Funders:	[7] Swiss National Science Foundation ; [UNSPECIFIED] European Cooperation in Science and Technology
Language:	English
Submitter:	Yiting Liu
Date Deposited:	06 Dec 2023 10:45
Last Modified:	06 Dec 2023 10:45
Publisher DOI:	https://doi.org/10.12688/openreseurope.16436.1
ARBOR DOI:	10.24451/arbor.20559
URI:	https://arbor.bfh.ch/id/eprint/20559