Traditional finance theories, grounded in the Efficient Market Hypothesis (EMH) and the assumption of rational investors, fall short in explaining the complex price movements and systematic deviations observed in financial markets. In this context, behavioral finance argues that investors are boundedly rational and that cognitive biases and emotional factors significantly influence decision-making processes. This study comprehensively examines the theoretical foundations of behavioral finance, the concept of bounded rationality, and the behavioral origins of market anomalies. Within the scope of the study, firm-characteristic-based anomalies, calendar effects, and price anomalies are classified, and the psychological mechanisms behind these deviations, such as overconfidence, representativeness, and conservatism, are discussed. Furthermore, current empirical findings in national and international literature, along with modern anomaly detection methods based on machine learning are evaluated. Consequently, within the framework of limits to arbitrage and investor sentiment, it is emphasized that market efficiency is weak contrary to theoretical predictions and that anomalies possess a persistent nature.