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The Impact of the Intensity of Government Intervention on the Stock price Prediction

Published: 28 June 2024 Publication History

Abstract

This paper proposes an innovative approach to quantify the intensity of government intervention in the stock market by extracting sentiment information from financial news using the FinBERT model. Specifically, the government's attitudes towards the stock market are classified into three types: intervention, no intervention, and ignorance. Firstly, we created a reliable dataset of 1229 news articles from 2005 to 2019 through manual annotation, using official news extracted from the front-page headlines of China Securities Journal as the original corpus. Then, we fine-tuned a Chinese FinBERT model based on this dataset to obtain a government intervention indicator for unlabeled news. Next, we integrated the government intervention indicator with other financial indicators to predict stock prices. Various machine learning models, including LSTM, CNN+LSTM, BiLSTM, Transformer, and others, were used to validate the effectiveness of this approach. The results demonstrate a significant improvement on the performance of stock price prediction. It can be reasonably argued that the intensity of government intervention is an indispensable factor for financial tasks.

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  1. The Impact of the Intensity of Government Intervention on the Stock price Prediction

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    ICRSA '23: Proceedings of the 2023 6th International Conference on Robot Systems and Applications
    September 2023
    335 pages
    ISBN:9798400708039
    DOI:10.1145/3655532
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 28 June 2024

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    Author Tags

    1. Fin BERT
    2. Fine-tuning
    3. Key words: Intensity of Government Intervention
    4. Sentiment analysis
    5. Stock price Prediction

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