然而，在FinNLP-2022 ERAI任务中:评估业余投资者基本原理的修正模型

Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP) Pub Date : 1900-01-01 DOI:10.18653/v1/2022.finnlp-1.17

Zhuang Yan, Fuji Ren

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引用次数: 1

摘要

财务报告通常反映公司最近的发展，并经常引起公司股价的波动。最大潜在收益较高和最大潜在损失较低的观点可以帮助业余投资者选择理性的投资策略。FinNLP-2022 ERAI任务旨在量化意见领先最大潜在利润更高和最大潜在损失更低的潜力。本文采用了不同的策略来解决ERAI任务。Valinna ' RoBERTa-wwm '表现出色，帮助我们在' MPP '标签预测任务中获得第二名。在整合了一些技巧后，改进后的“RoBERTa-wwm”在“ML”排名任务中表现优于所有其他模型。

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Yet at the FinNLP-2022 ERAI Task: Modified models for evaluating the Rationales of Amateur Investors

The financial reports usually reveal the recent development of the company and often cause the volatility in the company’s share price. The opinions causing higher maximal potential profit and lower maximal loss can help the amateur investors choose rational strategies. FinNLP-2022 ERAI task aims to quantify the opinions’ potentials of leading higher maximal potential profit and lower maximal loss. In this paper, different strategies were applied to solve the ERAI tasks. Valinna ‘RoBERTa-wwm’ showed excellent performance and helped us rank second in ‘MPP’ label prediction task. After integrating some tricks, the modified ‘RoBERTa-wwm’ outperformed all other models in ‘ML’ ranking task.

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Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)

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