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Generative AI Tools zur Prognose von Leitzins-Entscheidungen: eine Fallstudie am Beispiel der Leitzinsentscheidungen der Federal Reserve

Author

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  • Daube, Carl Heinz
  • Krivenkov, Vladislav

Abstract

Dieses Working Paper untersucht den Einsatz von Generative AI Anwendungen zur Prognose von Leitzinsentscheidungen der Federal Reserve. Es bewertet, ob diese Anwendungen eingesetzt werden können, um Leitzinsänderungen vorherzusagen, und vergleicht ihre Vorhersagegenauigkeit mit den Markterwartungen über einen Zeitraum von sechs Monaten.

Suggested Citation

  • Daube, Carl Heinz & Krivenkov, Vladislav, 2024. "Generative AI Tools zur Prognose von Leitzins-Entscheidungen: eine Fallstudie am Beispiel der Leitzinsentscheidungen der Federal Reserve," EconStor Preprints 293992, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:293992
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    File URL: https://www.econstor.eu/bitstream/10419/293992/1/Generative-AI-Tools-zur-Prognose-von-Leitzins-Entscheidungen.pdf
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    More about this item

    Keywords

    Künstliche Intelligenz; FED Leitzinsentscheidungen; large language model (LLM); natural language processing (NLP); Generative AI Anwendung ChatGPT; Generative AI AnwendungW Google Gemini;
    All these keywords.

    JEL classification:

    • G0 - Financial Economics - - General

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