04359ntm a22005297i 4500 000716550 CZ-PrVSE 20240914152213.0 m d cr n|||||||||| 240914s2024 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Starovoitov, Vitalii ISIS:157991 dis Analýza možnosti využití AI pro předpověď cen akcií a řady údajů z finančních výkazů sedmi největších společností podle kapitalizace v indexu Euro Stoxx 50 eng Analysis of the possibility of using AI to predict stock prices and a range of financial statement data from the seven largest-capitalization companies in the Euro Stoxx 50 index / Vitalii Starovoitov 2024 ?? stran : digital, PDF soubor Vedoucí práce: Laure Sabine Marie de Batz de Trenquelléon Bakalářská práce (Bc.)—Vysoká škola ekonomická v Praze. Fakulta mezinárodních vztahů, 2024 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2024 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. Způsob přístupu: Internet mezinárodní obchod [obor bakal. práce] bakalářské práce fd132403 czenas bachelor's theses eczenas Euro Stoxx 50 Index Machine Learning Models Stock Price Prediction Financial Forecasting Artificial Intelligence de Batz de Trenquelléon, Laure Sabine Marie ISIS:158001 ths Taušer, Josef ola20040322002 opn Vysoká škola ekonomická v Praze. Fakulta mezinárodních vztahů kn20010709400 dgg https://insis.vse.cz/zp/85533/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/85533 Hlavní práce https://insis.vse.cz/zp/85533/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/85533/posudek/oponent/83949 Oponentura https://insis.vse.cz/zp/85533/podrobnosti dc:identifier NEPOSILAT VSKP vse85533 240910 85533