Abstract
This paper presents a novel approach for explainability in financial analysis by utilizing the Pearson correlation coefficient to establish a relationship between aspect-based sentiment analysis and stock prices. The proposed methodology involves constructing an aspect list from financial news articles and analyzing sentiment intensity scores for each aspect. These scores are then compared to the stock prices for the relevant companies using the Pearson coefficient to determine any significant correlations. The results indicate that the proposed approach provides a more detailed and accurate understanding of the relationship between sentiment analysis and stock prices, which can be useful for investors and financial analysts in making informed decisions. Additionally, this methodology offers a transparent and interpretable way to explain the sentiment analysis results and their impact on stock prices. Overall, the findings of this paper demonstrate the importance of explainability in financial analysis and highlight the potential benefits of utilizing the Pearson coefficient for analyzing aspect-based sentiment analysis and stock prices. The proposed approach offers a valuable tool for understanding the complex relationships between financial news sentiment and stock prices, providing a new perspective on the financial market and aiding in making informed investment decisions.
Abstract (translated)
本论文提出了一种崭新的财务分析解释方法,利用皮尔森相关系数建立基于角度的情感分析与股票价格之间的关系。该方法涉及从财务新闻文章中构建角度列表,并对每个角度的情感强度得分进行分析。这些得分后与相关公司的股票价格使用皮尔森系数进行比较,以确定任何明显的相关关系。结果表明,该方法提供了更加详细和准确的理解情感分析和股票价格之间的关系,这对投资者和金融分析师在做出知情决策时非常有用。此外,该方法提供了一种透明和可解释的方式来解释情感分析结果及其对股票价格的影响。总而言之,本文的结论表明财务分析中解释的重要性,并突出了使用皮尔森系数分析基于角度的情感分析和股票价格的潜在好处。该方法提供了一个宝贵的工具,以理解金融新闻情感和股票价格之间的复杂关系,提供了对市场的新视角,并帮助做出知情的投资决策。
URL
https://arxiv.org/abs/2303.02563
