基于因果关系的多变量库存运动预测
Abel Díaz Berenguer1, Yifei Da1, Matías Nicolás Bossa1
1Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium.
PloS one
|April 25, 2024
概括
这项研究表明,金融新闻情绪显著影响国际股市. 动态转移 (DTE) 准确地捕获了这种信息流,提高了库存预测的准确性.
科学领域:
- 量化金融 量化金融
- 计算语言学 计算语言学
- 时间序列分析时间序列分析
背景情况:
- 了解金融新闻情绪与国际股市动态之间的相互依赖对于准确的预测至关重要.
- 现有的方法往往无法捕捉新闻情绪和市场行为之间的复杂因果关系和信息流.
研究的目的:
- 调查国际股票市场与金融新闻情绪之间的相互依赖,以改善股票预测.
- 引入动态转移 (DTE) 作为一种分析情绪和市场动态之间的信息流传播的新方法.
- 为了证明DTE信息的时间融合变压器 (TFT) 模型在股票价格和回报预测方面的优势.
主要方法:
- 利用FinBERT对财务新闻进行文字分析,以生成情绪时间序列.
- 使用转移和热图来分析净信息流.
- 计算动态转移 (DTE) 时间序列作为股票价格预测的共变量.
- 实施的时间融合变压器 (TFT) 用于使用DTE衍生信息进行股票市场预测.
主要成果:
- 拟议的基于DTE的因果关系方法与TFT集成,在股票价格和回报预测方面表现出卓越的准确性.
- 动态转移有效地确定了关键信息传播路径,包括市场峰值和突然跳跃.
- 该模型成功地结合了市场内部和市场间的相关性和信息流相互作用.
结论:
- 金融新闻情绪与国际股票市场的波动有着重要的因果关系.
- 动态转移是揭示金融时间序列中复杂信息流动动态的强大工具.
- 综合DTE和TFT方法为股票市场预测提供了强大而准确的方法.
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