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papersSEP 12 04:00 UTC

Context-Augmented LLMs Used to Improve Financial Forecasting with Alternative Data

A new arXiv paper examines how large language models can incorporate alternative data sources, such as consumer transactions, web traffic, and prediction markets, when forecasting a company's future financial performance. The authors argue these non-traditional signals offer timely insight into a firm's operating activity and propose augmenting LLMs with contextual information to make such data usable in forecasting tasks.

llm/finance/forecasting/alternative-data