Evaluation of the effectiveness of AI methods in detecting and forecasting anomalies in the stock ma

Music City Center 

Anomalies in the stock market, such as price manipulation, speculative bubbles or unusual capital flows, can lead to market destabilization. Traditional analysis methods, based on statistical models, often fail to keep up with the dynamic and complex nature of modern financial markets. The study aims to evaluate the effectiveness of artificial intelligence (AI) methods in detecting and forecasting stock market anomalies. AI can significantly improve the ability to monitor markets and provide early warnings of threats. The study will apply selected AI techniques to detect and analyze unusual market behavior.
Modern stock markets are characterized by a large number of market participants who generate a large number of transactions and a large amount of information. This situation means that traditional methods of analysis, based, for example, on econometric models and simple financial indicators, are often unable to identify risks associated with stock market anomalies on time. In this respect, artificial intelligence tools can be helpful. The study used data on selected companies listed on stock exchanges in the Baltic countries. The data covered the years 2007-2024.

AI

econometric models

stock market anomalies

stock market indices 

Section on Risk Analysis