Financial Market Automatic Prediction Using News Articles
In recent years, the financial markets have increased popularity, driven in large part by internet access and online trading platforms. This surge has not only increased the number of market participants but has also amplified the impact of information dissemination on stock prices. This thesis expl...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/410909 |
| Acceso en línea: | https://hdl.handle.net/2117/410909 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial intelligence Machine learning Natural language processing (Computer science)) Artificial Intelligence natural language processing Intel·ligència artificial Aprenentatge automàtic Tractament del llenguatge natural (Informàtica) Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
| Sumario: | In recent years, the financial markets have increased popularity, driven in large part by internet access and online trading platforms. This surge has not only increased the number of market participants but has also amplified the impact of information dissemination on stock prices. This thesis explores to relate fundamental analysis and technical analysis thanks to artificial intelligence (AI). The fundamental analysis traditionally associated with financial health, and market prediction with technical analysis which is the price chart movement. Our models will try to predict financial market with help of news articles. Currently, AI models have emerged as indispensable tools for processing massive information sources. Machine learning algorithms (ML), natural language processing (NLP) and sentiment analysis enable the automate extraction in massive text data information. The importance of news articles in financial market prediction cannot be underestimated. News items, both traditional and social media, have the power to rapidly influence investor sentiment and, consequently, asset prices. This thesis delves into the role of sentiment expressed in news articles translated to the price movement. Online articles platforms can shape investor behavior converting either bullish (up trend) or bearish (down trend) trends. |
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