Analýza možnosti využití AI pro předpověď cen akcií a řady údajů z finančních výkazů sedmi největších společností podle kapitalizace v indexu Euro Stoxx 50

The main focus of this bachelor thesis will be to examine the potential of applying Artificial Intelligence (AI) in the prediction of stock prices and other financial metrics of the largest seven capitalization companies within the Euro Stoxx 50 index. The research question is to determine the efficiency of the chosen AI models namely OpenAI’s ChatGPT, Google’s Gemini and Microsoft’s Copilot in the prediction of financial metrics such as revenues, net income, stock price, P/E ratio, D/E ratio, ROE and P/Debt ratio. The objective of the present research is to determine the accuracy of the AI models in financial prediction by comparing the models’ estimates with the actual financial figures. The research methodology involves a discussion of the literature review that focuses on the application of AI in finance, specifically, machine learning and the same’s application in predicting stock prices. The data used in the study is historical financial data that is obtained from the reliable databases such as Yahoo Finance and the models that are developed to predict the market's future. The performance of each model is evaluated based on the accuracy of the financial metrics’ prediction and the outcomes are then presented to highlight the strengths and weaknesses of the models and the implications. This paper shows that with AI models such as ChatGPT, revenues and net profit could be faithfully estimated, but other aspects had large errors; hence the need for more enhancement. The research finds out that in the field of finance, human contribution should be integrated with the AI outputs in the decision-making process. In addition, the study also provides possible problems in AI where these are data quality issues, interpretability of the model, and ethical issues in order to support the development and the ethical standard of AI. Lastly, the thesis states the benefits and drawbacks of applying the contemporary AI techniques in financial forecasting and the avenues for future research.