Short Interest Trend Prediction with Large Language Models
Zhaomin Xiao, Zhelu Mai, Yachen Cui, Zhuoer Xu, Jiancheng Li
Abstract
This paper studies the problem of short interest trend prediction using large language models. To do so, we provide a formal task definition and create a dataset for this task. We conduct extensive experiments with various types of large language models in different settings of in-context learning. Our results show that large language models have gained knowledge pertaining to short sale interest trends, and providing examples is beneficial.
Topics & Concepts
Computer scienceArtificial intelligenceNatural language processingTopic ModelingComputational and Text Analysis MethodsSentiment Analysis and Opinion Mining