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Supervisor

Stock Market Predictions through Deep Learning

Status: open / Type of Theses: Bachelor Theses, Master theses / Location: Dresden

This topic focuses on a collaboration with Orca Capital, a company specializing in financial markets. Together with Orca Capital, a Munich-based startup has developed a runing system that predicts the stock prices of certain companies based on a continuous stream of news, such as rising/falling prices and volatility. This system utilizes deep learning and natural language processing methods, including pretrained language models. The students will work on further developing and enhancing the system, using real-world financial data and industry contacts. Possible enhancements include applying the latest language models (LLMs) and techniques to make the predictions more explainable (explainable AI).

What are the tasks?

  • Developing extensions and improvements of the system, using the latest findings in deep learning and natural language processing.
  • Evaluating the system’s performance and making its predictions more interpretable, integrating methods from the field of explainable AI.

What prerequisites do you need?

  • Good programming skills in Python.
funded by:
Gefördert vom Bundesministerium für Bildung und Forschung.
Gefördert vom Freistaat Sachsen.