Corporate Event Predictions Using Large Language Models

This paper offers a thorough assessment of large language models (LLMs) in the context of corporate event prediction. To achieve this, we formally establish the task of corporate event prediction, construct a novel dataset containing summaries of earning call transcripts, and conduct comprehensive e...

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Bibliographic Details
Main Authors: Xiao, Zhaomin, Mai, Zhelu, Xu, Zhuoer, Cui, Yachen, Li, Jiancheng
Format: Conference Proceeding
Language:English
Subjects:
corporate events
large language models
Machine intelligence
natural language processing
Predictive models
Task analysis
Online Access:Request full text
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Summary:This paper offers a thorough assessment of large language models (LLMs) in the context of corporate event prediction. To achieve this, we formally establish the task of corporate event prediction, construct a novel dataset containing summaries of earning call transcripts, and conduct comprehensive experiments involving both raw and fine-tuned variants of the primary LLMs. Our experimental findings underscore the viability of automating this intricate task using LLMs and highlight the unnecessariness of additional finetuning.
ISSN:2640-0146
DOI:10.1109/ISCMI59957.2023.10458651