Quantifying Uncertainty: A New Era of Measurement through Large Language Models

Francesco Audrino, Jessica Gentner and Simon Stalder
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Francesco Audrino: University of St. Gallen; Swiss Finance Institute

No 24-68, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: This paper presents an innovative method for measuring uncertainty using Large Language Models (LLMs), offering enhanced precision and contextual sensitivity compared to the conventional methods used to construct prominent uncertainty indices. By analyzing newspaper texts with state-of-the-art LLMs, our approach captures nuances often missed by conventional methods. We develop indices for various types of uncertainty, including geopolitical risk, economic policy, monetary policy, and financial market uncertainty. Our findings show that shocks to these LLM-based indices exhibit stronger associations with macroeconomic variables, shifts in investor behaviour, and asset return variations than conventional indices, underscoring their potential for more accurately reflecting uncertainty.

Keywords: Large Language Models; Economic policy; Geopolitical risk; Monetary policy; Financial markets; Uncertainty measurment (search for similar items in EconPapers)
JEL-codes: C45 C55 E44 G12 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2024-08
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp and nep-rmg
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Related works:
Working Paper: Quantifying uncertainty: a new era of measurement through large language models (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2468

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