Anticipating Corporate Financial Performance from CEO Letters Utilizing Sentiment Analysis

Table 3

Related work of forecasting financial performance using textual information.

Authors	Material	Period	Methods	Key findings
Loughran and Mcdonald [42]	Annual report	1994–2008	Sentiment dictionary	Textual analysis can contribute to the ability to understand the impact of information on stock returns. Most importantly, researchers should be cautious when relying on word classification scheme derived outside the domain of business usage.
Schumaker et al. [43]	Financial news articles	2005	Machine learning	The financial news article prediction system can predict price increase or decrease in sentiment analysis with the accuracy of approximately 50%.
Hájek and Olej [44]	520 U.S. companies’ annual report	2010	Machine learning	Sentiment information in annual reports can significantly improve the accuracy of the used classifiers.
Xin et al. [45]	U.S. manufacturing industry annual report	1997–2003	Machine learning	Using machine-learning approach employed with the results of text analysis can predict next year’s earnings per share.
Hájek et al. [46]	448 U.S. companies’ annual report	2008	Machine learning; neural networks	Sentiment information is an important determinant for forecasting financial performance.
Tong et al. [47]	Microblogs in China	2016.2–2016.9	Machine learning	There is a strong correlation between chat room postsentiment and stock price movement.