确定情绪指数与股价收益的超前-滞后结构

Alex Momotov, Xianghua Xie
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引用次数: 0

摘要

本研究对比和比较了新闻情感分析领域内两种方法的最新技术,并研究了一种新的“TF-IDF动量矩阵”的文档编码表示。所提出的基于词典的方法以Loughran & McDonald金融情绪词表为中心,达到86.4%的解释股票动量方差,而分类方法遵循实施潜在狄利克雷分配的主题分析管道,达到94.8%。作为模型评估的附加元素,研究实现了热最优路径方法,该方法依赖于动态规划方法进行性能优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining Lead-Lag Structure between Sentiment Index and Stock Price Returns
This research contrasts and compares the state-of-the-art techniques of the two approaches within the domain of news sentiment analysis, as well as, investigates a novel document encoding representation of the 'TF-IDF momentum matrix'. The presented lexicon-based methodology is centred around Loughran & McDonald financial sentiment word lists and reaches 86.4% explained stock momentum variance, whereas the classification approach follows a thematic analysis pipeline implementing Latent Dirichlet Allocation and achieves that of 94.8%. As an additional element of model evaluation, the research implements Thermal Optimal Path method which relies on a dynamic programming approach for performance optimisation.
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